Adaptive Spectral Forecast [WillyAlgoTrader]📡 Adaptive Spectral Forecast is an overlay indicator that applies Goertzel spectral analysis to decompose price into its dominant cyclical components, reconstructs them as a harmonic sum, and then extrapolates the resulting waveform forward in time to generate a visual forecast with confidence bands. Signals fire when the forecast direction changes with sufficient signal-to-noise ratio and trend alignment — projecting where price is likely to oscillate next based on the cycles detected in recent history.
This is a fundamentally different approach from trend-following or momentum-based indicators. Instead of asking "where is price going based on its direction and speed?", spectral analysis asks "what recurring cycles exist in this price data, and where do they project to next?" The Goertzel algorithm is a targeted frequency detector — it scans a range of cycle periods, measures the power (amplitude²) at each frequency, identifies the dominant peaks, computes their exact phase and amplitude via DFT projection, and recombines them into a multi-harmonic forecast that decays toward the adaptive trend as it extends into the future.
🧩 WHY THESE COMPONENTS WORK TOGETHER
Raw price is a mix of trend, cycles, and noise. Attempting to forecast raw price directly fails because trend and cycles require different extrapolation methods: trend continues linearly, cycles repeat sinusoidally, and noise should not be extrapolated at all.
This indicator solves the problem through decomposition and reassembly:
EMA trend extraction → Hann-windowed detrending → Goertzel spectral scan → SNR peak detection → DFT coefficient extraction → Harmonic recombination with decay → Trend re-addition → Confidence bands
Each stage addresses a specific challenge:
— Trend extraction separates the slow directional component so it can be extrapolated linearly (via slope), not sinusoidally
— Hann windowing reduces spectral leakage — without it, the finite data window creates false frequency peaks that contaminate the analysis
— Goertzel scanning efficiently measures power at each candidate frequency without computing a full FFT — enabling targeted, adaptive-resolution frequency detection
— SNR filtering ensures only cycles with meaningful signal strength are included — weak noise-level frequencies are discarded
— DFT coefficient extraction computes the exact amplitude and phase of each selected cycle on un-windowed data (the Hann window is only for spectral scanning, not for coefficient calculation — this preserves correct amplitudes)
— Harmonic decay causes the cyclic component to gradually fade toward the trend as the forecast extends forward — reflecting the reality that detected cycles have limited persistence
— Confidence bands widen with √(bars ahead) × ATR, showing that forecast uncertainty grows with distance
Removing any component breaks the pipeline: without detrending, the Goertzel scan detects the trend as a low-frequency "cycle". Without Hann windowing, spectral leakage creates phantom peaks. Without SNR filtering, the forecast includes noise-level harmonics that produce random oscillations. Without decay, the harmonic projection repeats forever at full amplitude (unrealistic). The full pipeline is required.
🔍 WHAT MAKES IT ORIGINAL
1️⃣ Goertzel spectral analysis for cycle detection.
The Goertzel algorithm is a single-frequency DFT that computes the power at one specific period using a recursive formula:
s0 = data + 2×cos(2π/period) × s1 − s2
After iterating through all N data points, the power is: (s1 − s2×cos(ω))² + (s2×sin(ω))², normalized by N² for cross-period comparability.
The indicator scans every integer period from Min Cycle Period (default 8) up to N/2, with an adaptive step size: every period for fast cycles (≤30 bars), step of 2 for longer cycles (reducing computation without losing resolution where it matters most). For each period, the Goertzel power is computed, producing a power spectrum — a map of which cycle lengths carry the most energy in the current price data.
This is fundamentally more targeted than an FFT. An FFT computes power at all frequencies simultaneously but at fixed resolution (determined by window size). The Goertzel approach allows scanning exactly the frequency range of interest with customizable resolution.
2️⃣ SNR-based peak detection with fallback.
From the power spectrum, the indicator identifies local peaks (frequencies where power is higher than both neighbors) and computes the Signal-to-Noise Ratio for each: SNR = peak_power / mean_power_across_all_frequencies. Only peaks with SNR ≥ Min Cycle SNR (default 2.0) are accepted as genuine cycles — the rest are considered noise-level fluctuations.
If no peaks pass the SNR filter (possible in highly random or trend-dominated price action), the algorithm falls back to the single strongest frequency. In this case, the dashboard displays "Weak*" strength and buy/sell signals are suppressed — the forecast is shown for visual reference only, but the indicator acknowledges that no reliable cyclical structure was found.
The top N peaks (sorted by power, N = Harmonics Count, default 5) are selected as the dominant cycles.
3️⃣ DFT coefficient extraction on un-windowed data.
For each selected cycle period, the indicator computes exact sine and cosine coefficients using standard DFT projection:
a = (2/N) × Σ data × sin(2π × i / period)
b = (2/N) × Σ data × cos(2π × i / period)
Critically, this computation uses the raw detrended data (without Hann windowing). The Hann window was only applied for the spectral scan (to identify which frequencies are dominant). Using windowed data for coefficient extraction would distort the amplitude of the harmonics. This two-pass approach — windowed scan for detection, raw data for coefficients — is a key design choice that preserves forecast accuracy.
4️⃣ Harmonic extrapolation with configurable decay.
The forecast is constructed by evaluating the harmonic sum at each future bar:
forecast = trend_projection + Σ (a_k × sin(ω_k × t) + b_k × cos(ω_k × t)) × decay^(t − t_base)
Where trend_projection = trend_last + trend_slope × bars_ahead (linear extrapolation of the EMA trend). The decay factor (default 0.97) causes harmonic amplitude to reduce by 3% per bar, so the cyclic component gradually fades and the forecast converges toward the trend line.
At decay = 1.0, harmonics repeat at full amplitude forever (pure cycle projection). At decay = 0.95, they fade rapidly (forecast becomes trend-only within ~20 bars). Default 0.97 provides meaningful oscillation for the first 20–30 bars before fading. The forecast line is colored by segment: green segments where the forecast is rising, red where falling. Reversal dots mark predicted peaks and troughs.
5️⃣ ATR-based confidence bands with √t scaling.
Uncertainty in the forecast grows with distance. The confidence band width is calculated as:
band_width = ATR(14) × confidence_multiplier × √(bars_ahead)
The √t scaling follows the mathematical principle that forecast variance grows linearly with time horizon (standard deviation grows with square root). The ATR provides the natural volatility scale of the instrument. At bar +1, the band is approximately ATR × multiplier. At bar +25, it's 5× wider. This gives a realistic visual envelope of where price might actually be, not just the central harmonic forecast.
6️⃣ 3-bar consensus forecast direction.
Instead of using a simple "is the next bar higher or lower?" check (which is noisy), the forecast direction is determined by majority vote over 3 bars:
The indicator evaluates the forecast at t+0, t+1, t+2, t+3 and counts upward moves: upVotes = (y1>y0 ? 1:0) + (y2>y1 ? 1:0) + (y3>y2 ? 1:0). If ≥2 of 3 transitions are upward → forecast direction is bullish. If ≤1 → bearish. This consensus approach prevents a single-bar oscillation from flipping the forecast direction.
7️⃣ Trend alignment filter for signal quality.
When enabled (default on), buy signals require the EMA trend slope to be positive, and sell signals require negative slope. This prevents the indicator from generating counter-trend signals when a cycle oscillation temporarily points against the broader trend — which is the most common source of false signals in cycle-based systems.
If the trend filter blocks a direction change, the forecast visualization still updates (you can see the cycle projection) but no signal label is emitted. Additionally, signals are suppressed when the SNR is below the minimum threshold or when the spectral scan fell back to a single non-significant frequency.
8️⃣ Adaptive trend extraction with linear extrapolation.
The trend component is extracted using an EMA with configurable smoothing (default 30 bars), applied forward using the buildTrendArray function. The trend's slope is computed via weighted linear regression over the last 5 points of the trend array — providing a stable slope estimate that isn't dominated by a single bar.
The trend is extrapolated linearly into the forecast: trend_forecast = trend_last + slope × i. This linear projection is appropriate for the short-term forecast horizon (15–55 bars) where trend curvature is typically negligible.
9️⃣ Historical fit visualization.
The reconstructed harmonic sum + trend is plotted over historical data as a polyline, showing how well the detected cycles explain the actual price movement. This serves as an immediate visual validation: if the fit tracks price well, the detected cycles are meaningful. If the fit diverges significantly, the current market regime may not have strong cyclical structure (reflected in low SNR scores in the dashboard).
The fit line is colored by trend direction (green for bullish slope, red for bearish) and decimated for performance (every 1–3 bars depending on lookback length).
🔟 Four presets with coordinated parameter scaling.
— Conservative : lookback ≥ 150, harmonics ≤ 3, forecast ≥ 40 bars — stable, long-term cycles, less overfitting risk
— Default : user settings unchanged
— Aggressive : lookback ≤ 80, harmonics +1, forecast ≤ 25 — faster adaptation, more cycles included
— Scalping : lookback ≤ 50, harmonics +2, forecast ≤ 15 — shortest window, most harmonics, very short projection
Each preset adjusts lookback (spectral window), harmonics count (complexity), and forecast length (projection horizon) as a coordinated unit. Longer lookback needs fewer harmonics (the cycles are more stable). Shorter lookback needs more harmonics (to capture the faster fluctuations within the compressed window).
⚙️ HOW IT WORKS — CALCULATION FLOW
Step 1 — Data collection: The last N bars (Analysis Lookback, default 144) of the selected price source are collected into an array, oldest first.
Step 2 — Trend extraction: An EMA with the Trend Smoothing period (default 30) is applied across the array using a forward-pass recursive formula: trend = α × price + (1−α) × trend . This produces a smooth trend array.
Step 3 — Detrending + Hann window: Each bar's trend value is subtracted from its price. The residual is multiplied by a Hann window: w = 0.5 × (1 − cos(2π×i/(N−1))). This isolates the cyclical component while minimizing spectral leakage at the data boundaries.
Step 4 — Goertzel spectral scan: For each candidate period from minPeriod to N/2 (adaptive step: 1 for periods ≤30, 2 for longer), the Goertzel algorithm computes power. The result is a power spectrum across all scanned frequencies.
Step 5 — Peak detection: Local maxima in the power spectrum are identified (power > both neighbors). Each peak's SNR is computed against the mean power. Peaks with SNR ≥ threshold are accepted. If none pass, the strongest single frequency is used as fallback (with "Weak*" marking).
Step 6 — Coefficient extraction: For the top N peaks (by power), sine and cosine coefficients are computed via DFT projection on raw (un-windowed) detrended data. This gives exact amplitude and phase for each cycle.
Step 7 — Forecast generation: The trend is extrapolated linearly using its 5-bar regression slope. Each harmonic is evaluated at future time steps with decay applied. The sum of trend + decayed harmonics produces the central forecast line. Confidence bands = ATR × multiplier × √(bars_ahead).
Step 8 — Direction and signals: 3-bar consensus determines forecast direction. Trend filter and SNR check gate signal emission. Buy/sell labels appear on bar-close confirmation.
📖 HOW TO USE
🎯 Quick start:
1. Add the indicator — the historical fit and forecast line appear on the last bar
2. The colored dotted line extending right is the forecast (green = rising, red = falling)
3. Colored dots (●) on the forecast mark predicted peaks and troughs
4. Dotted lines above and below = confidence bands (forecast uncertainty zone)
5. ▲/▼ labels = buy/sell signals when the forecast direction changes
👁️ Reading the chart:
— 🟢 Green solid line on history = harmonic fit (uptrend slope)
— 🔴 Red solid line on history = harmonic fit (downtrend slope)
— 🟢🔴 Dotted line extending right = forecast (colored by direction: green rising, red falling)
— 🔵 Upper/lower dotted lines = confidence bands (uncertainty grows with distance)
— 🟢 ● dots = predicted troughs (potential support)
— 🔴 ● dots = predicted peaks (potential resistance)
— 🟢 ▲ below bar = buy signal (forecast changed to bullish)
— 🔴 ▼ above bar = sell signal (forecast changed to bearish)
📊 Dashboard fields:
— Trend: current EMA trend direction (Bullish / Bearish / Neutral)
— Forecast: predicted direction (▲ Up / ▼ Down / — Flat)
— Signal: current state (BUY / SELL / Bullish Bias / Bearish Bias / Wait)
— Strength: cycle quality based on average SNR (Strong > 5.0 / Medium > 2.5 / Weak / Weak* = fallback)
— Dom. Cycle: dominant cycle period in bars (e.g., "34 bars")
— Cycles: how many cycles passed SNR filter vs. requested (e.g., "3 / 5")
— Timeframe, preset, version
🔧 Tuning guide:
— Forecast too noisy: reduce Harmonics Count (3), increase Min SNR (3.0+), increase Trend Smoothing
— Forecast too smooth: increase Harmonics Count (5–7), decrease Min SNR (1.5), decrease Trend Smoothing
— Cycles don't match price: increase Analysis Lookback (200+) for more stable cycle detection, or decrease for faster adaptation
— Forecast fades too fast: increase Decay Rate toward 0.99–1.0
— Forecast unrealistic long-term: decrease Decay Rate toward 0.95, reduce Forecast Bars
— Too many false signals: enable Trend Alignment Filter, increase Min SNR
— Scalping 1–5M: use Scalping preset (lookback ≤50, 7 harmonics, 15-bar forecast)
— Swing 4H–1D: use Conservative preset (lookback ≥150, 3 harmonics, 40-bar forecast)
⚙️ KEY SETTINGS REFERENCE
⚙️ Main:
— Analysis Lookback (default 144): spectral analysis window — the last N bars analyzed
— Harmonics Count (default 5): how many dominant cycles to include in the forecast
— Min Cycle Period (default 8): shortest cycle to scan for (bars)
— Preset (default Default): Conservative / Default / Aggressive / Scalping
— Trend Alignment Filter (default On): require trend-forecast agreement for signals
🔮 Forecast:
— Forecast Bars (default 55): projection length into the future
— Confidence Band Width (default 1.5× ATR): band multiplier
— Trend Smoothing (default 30): EMA period for trend component
— Harmonic Decay Rate (default 0.97): amplitude reduction per bar (1.0 = no decay)
— Min Cycle SNR (default 2.0): signal-to-noise threshold for cycle acceptance
🎨 Visual:
— Historical fit, trend line, reversal dots, confidence bands (all toggleable)
— Auto / Dark / Light theme
🔔 Alerts
— 🟢 BUY — ticker, price, timeframe, time
— 🔴 SELL — same fields
Both support plain text and JSON webhook format. Signals are bar-close confirmed, direction-locked, trend-filtered, and SNR-gated.
⚠️ IMPORTANT NOTES
— 📐 This is spectral analysis, not trend following. The indicator detects and projects recurring cycles. In markets with strong cyclical structure (commodities, forex majors, crypto with regular oscillations), it performs well. In news-driven or momentum-dominated markets with no cyclical structure, the SNR will be low and the forecast unreliable — the dashboard reflects this via the Strength reading.
— 🚫 No repainting of signals. The spectral analysis runs on barstate.islast (updating the forecast in real time on the current forming bar). Signals only fire on the next barstate.isconfirmed bar, after the forecast direction has been set. This means the forecast line itself updates in real time (by design — it's a live projection), but buy/sell signals are confirmed and do not change retroactively.
— 📊 The forecast is a projection, not a prediction. It shows where price would go if the detected cycles continue with their current amplitude and phase. Real markets introduce new information that disrupts cycles. The confidence bands reflect this growing uncertainty. Treat the forecast as a probabilistic zone, not a target.
— 🔄 "Weak*" strength means no cycles passed the SNR filter and the indicator fell back to the single strongest frequency. In this state, signals are suppressed. The forecast is still shown for visual reference but should not be trusted for trading decisions.
— ⚖️ The Hann window is applied only for spectral scanning , not for coefficient extraction. This is deliberate: the window prevents spectral leakage during frequency detection, but the un-windowed data preserves correct harmonic amplitudes for the forecast.
— 📏 The forecast extends a fixed number of bars into the future. Accuracy degrades with distance — the first 10–15 bars are typically the most reliable. The confidence bands quantify this degradation visually.
— 🛠️ This is a spectral analysis and forecasting tool , not an automated trading bot. It detects cycles, projects them forward, and generates directional signals — trade decisions remain yours.
— 🌐 Works on all markets and timeframes. Cycle periods adapt automatically to whatever timeframe you apply it on. Indicator
6 EMA Setup**6 EMA Setup** is a multi-moving-average indicator designed to help traders quickly read **trend direction, pullback zones, and long-term market structure** using six Exponential Moving Averages on a single chart.
The indicator comes with default EMA lengths of **9, 21, 34, 89, 200, and 500**, allowing traders to monitor both **short-term momentum** and **higher-timeframe trend alignment** in one view.
A key visual feature of this setup is that the **9 EMA and 21 EMA are displayed as solid lines**, making the fast trend and immediate momentum easy to follow, while the higher EMAs are displayed in a **dashed style** to separate broader trend structure from short-term action.
### Default EMA setup
* **EMA 9** – fast momentum
* **EMA 21** – short-term trend
* **EMA 34** – pullback/trend support zone
* **EMA 89** – medium-term structure
* **EMA 200** – major trend direction
* **EMA 500** – higher trend bias / macro structure
### Features
* 6 configurable EMA lines
* Default lengths: **9, 21, 34, 89, 200, 500**
* Individual **show/hide toggle** for each EMA
* Custom **color setting** for every EMA
* **Solid lines** for 9 and 21 EMA
* **Dashed style** for 34, 89, 200, and 500 EMA
* Adjustable **source**
* Adjustable **offset**
* Customizable dash/gap appearance for dashed EMAs
### How it helps
This indicator is useful for:
* Identifying **trend direction**
* Tracking **short-term momentum shifts**
* Spotting **pullback entries**
* Understanding **trend continuation zones**
* Filtering trades with **higher-timeframe EMA alignment**
* Visualizing whether price is trading above or below key dynamic support/resistance levels
### Common use case
Many traders use this type of EMA stack to check:
* whether **9 is above 21** for momentum strength
* whether price respects **34 or 89** during pullbacks
* whether market is above or below **200 EMA** for main trend bias
* whether the **500 EMA** supports the larger directional context
### Best for
* Trend-following traders
* Pullback traders
* Intraday traders
* Swing traders
* Multi-timeframe chart readers
If you want, I can also give you:
* a **short PulseWire publish description**
* a **professional/public library description**
* a **simple beginner-friendly description**
* or a **combined description** for your **Donchian + EMA indicator**
Indicator
Indicator
Wirezard Wave RiderWirezard Wave Rider
🚀 Release Notes
This update introduces a major overhaul to the signal engine, moving away from unanimous consensus toward a more responsive Weighted Multi-Timeframe (MTF) approach. We’ve also integrated advanced divergence detection and Fibonacci structure tracking to better identify wave transitions.
🧠 Core Engine & Logic Upgrades
Weighted MTF Scoring: Replaces the old "unanimous consensus" logic. This significantly reduces lag at market tops and bottoms, allowing for more agile entries and exits.
VIDYA Trend Integration: The Variable Index Dynamic Average (VIDYA) is now woven into all signal tiers, MTF calculations, and divergence checks for unified trend confirmation.
Pivot-Based Structure Tracking: New swing high/low logic provides the script with "wave awareness," allowing it to identify market structure shifts in real-time.
📉 Precision Analysis Tools
Divergence Detection: Automated RSI and MACD divergence tracking to catch Wave 3/5 tops and Wave A/C bottoms.
Fibonacci Retracement Overlays: Dynamic Fib levels are now drawn from the most recent major swing, serving as both a visual guide and a signal modifier.
Dynamic RSI Thresholds: Adjusted tightRsiSell from 40 to 52, enabling much earlier detection of corrective moves.
⚡ New Signal Tiers
SELL Tier 3 (Early Divergence): A preemptive signal that fires at market tops before the trend officially flips, based on bearish divergence.
BUY Tier 2 (Correction Buy): Specifically designed to catch Wave 2, 4, or B bottoms using relaxed MTF requirements to ensure you don't miss the bounce.
🖥️ UI & Notifications
Expanded MTF Dashboard: The on-screen display now includes real-time divergence status and swing structure information.
Enhanced Alert Payloads: Standardized alert messages now include the specific Signal Tier and Divergence Data, making it easier to automate or triage notifications. Indicator
Tectonic [The_lurker]◈ Tectonic — Market State Architecture - هندسة حالة السوق ◈
The earth beneath your chart is not solid. It shifts. It cracks. It builds pressure for weeks — then breaks in seconds.
Tectonic does not watch price. It listens to the ground underneath.
Every market sits on invisible layers of energy, control, and absorption. When these layers align, trends run smooth. When they diverge, the surface holds — but the fault lines spread silently beneath. Then comes the break.
Tectonic reads this. Every bar, it answers three questions:
→ What is the current structural state?
→ Can it hold?
→ Where are the fault lines forming?
This is not an indicator. This is a seismograph for market structure.
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🔬 THE THREE TECTONIC LAYERS
Most indicators see one layer — price. Tectonic sees three:
⚡ Energy (E)
The raw force driving the market. Measured by rate-of-change magnitude, normalized through percentile ranking. High energy means the ground is moving with conviction. Low energy means the surface is quiet — but quiet does not mean safe.
⚖️ Control (S)
Which side owns the momentum — buyers or sellers? This uses asymmetric windowed analysis to detect when the balance of power shifts between hands — often before price shows it. Above 60% means buyer dominance. Below 40% means seller dominance. Near 50% means a contested fault line.
🧲 Absorption (A)
How much pressure is the ground absorbing without releasing? This is the layer most traders never see. High absorption during a trend means the rock is saturated — it cannot hold more, fracture is near. High absorption during a range means compression is building — the release will be violent. The lambda parameter reads absorption differently in trends versus ranges.
These three form the tectonic field. Not price action. Not candle patterns. The actual forces moving beneath your chart.
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🧬 STRUCTURAL TILT (α)
Beneath the noise of individual bars, which way does the continent lean?
Alpha measures the persistent imbalance between upward and downward momentum over a long structural window. Think of it as geological tilt — the deep directional bias that survives daily turbulence.
⦿ Strong positive — the foundation tilts bullish
◉ Moderate — mild directional lean
◎ Near zero — flat terrain, no structural bias
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🔺 SEISMIC ACCELERATION (RA)
The tremors are increasing. Something is about to shift.
RA measures how fast the entire tectonic field is moving — Energy, Control, and Absorption all at once:
RA = percentile_rank( |delta E| + |delta S| + |delta A| )
Low RA means geological calm. High RA means seismic activity — the plates are grinding. It does not tell you which way the break will go. It tells you the break is coming.
This is what lets Tectonic detect regime shifts before they become visible on the surface.
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◆ PLATE ROTATION (θ, Δθ)
The tectonic plates do not just push — they rotate.
Tectonic maps the relationship between Energy and Control changes onto a circular field:
theta = atan2(delta S, delta E)
Four rotational phases. Four colors. Four meanings:
🟠 Thrust Phase (0 to 45 and 315 to 360 degrees)
The plates are pushing hard in one direction. Energy rising, control locked. This is the acceleration phase — momentum builds with clear force.
🟢 Transfer Phase (45 to 135 degrees)
The balance is shifting. One plate subducting under another. Power transferring from buyers to sellers or vice versa. The surface has not cracked yet — but the pressure point is moving.
🔵 Subsidence Phase (135 to 225 degrees)
The driving force is fading. The old plate still holds position but has no energy left. This is structural decay — the trend is sinking, not breaking.
🔴 Collapse Phase (225 to 315 degrees)
Neither plate holds. Structural chaos. No conviction from either side. This is where false signals live — and where the next regime emerges from the rubble.
When rotation accelerates rapidly (high |delta theta|), a Tectonic Reversal ⟳ triggers — the clearest warning that the plates are about to snap.
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🧱 ADAPTIVE STABILITY
Is the ground solid — or is it standing on a fault line?
Stability combines three destabilizing forces into one reading:
stabilityBase = 1 - (RA x 0.4 + |delta theta| / pi x 0.4 + A x 0.2)
But a reading means nothing without context. A 70% stability reading on a 3-bar-old regime is sand. The same 70% after 50 bars of persistence is bedrock. So Tectonic scales it:
stability = stabilityBase x (0.5 + maturity x 0.5)
Young formations earn half credit. Ancient formations earn full credit. This is geological thinking — old rock is stronger than fresh sediment.
Notice: Absorption is a hidden stress factor. A mature formation with high absorption looks solid but is actually saturated. Tectonic detects this. Traditional indicators see a stable market. Tectonic sees a dam about to break.
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⏳ FORMATION MEMORY
How old is this geological formation? And is it aging into granite — or crumbling into dust?
Two independent clocks:
Regime Age — how many bars the current state has persisted.
Plate Age — how many bars the rotational phase has stayed in the same quadrant.
When both are old together, the structure is cohesive. When they diverge — regime stable but plates rotating wildly — the surface looks calm but underground fractures are spreading.
Formation classification:
🌱 Less than 5 bars — Fresh (unproven, fragile)
📈 5 to 20 bars — Forming (gaining density)
🏛️ 20 to 50 bars — Established (reliable, load-bearing)
⏳ More than 50 bars — Ancient (powerful but brittle under new stress)
Stability trend shows whether the formation is hardening ↑, holding →, or eroding ↓.
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🔻 FRACTURE INDEX (SPI)
This is why Tectonic exists. Everything else builds to this moment.
phaseFrag = 1 - min(phaseDuration / regimeDuration, 1)
SPI = regimeMaturity x phaseFrag x (1 - stability)
The Fracture Index detects silent cracks. Picture this:
A bullish trend has held for 60 bars. Price looks strong. RSI looks healthy. MACD looks fine. Every traditional indicator says hold.
But underground — the plates are rotating wildly inside a stable regime. Stability is dropping bar by bar. The formation has been standing so long it has become brittle.
The Fracture Index sees this. It rises quietly. At 35% — hairline cracks. At 60% — the Outlook flips to Internal Fracture. Then the break comes — fast, clean, devastating. Invisible to everyone watching the surface.
The Fracture Heatmap paints this directly on your chart. Nothing visible when pressure is low. A faint amber glow as stress builds. Deep red as the fault line reaches critical mass. You feel the earthquake coming before the ground moves.
◇ Below 35% — Stable ground. Formation is sound.
⚠️ 35 to 60% — Stress building. Micro-fractures forming.
🔻 Above 60% — Critical. The break is imminent.
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📋 COMMAND CENTER
Two modes for two mindsets:
Full Mode (18 rows) — for the geologist who wants every layer visible:
Structural tilt with bias, E S A with percentage and gauge, seismic acceleration, last signal details (plate color, direction, reversal status, age), current regime, formation memory with age and maturity and stability trend, adaptive stability with gauge, plate age with phase name, fracture index with gauge, and tectonic outlook.
Simple Mode (5 rows) — for the trader who needs one glance:
Regime with direction and formation age, stability with fracture warning, E S A compact, and outlook.
Switch anytime in settings under Mode.
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📊 TECTONIC STATES
▲ Bullish Drift — High E, Bullish S, Low A — Clean continental drift upward.
▼ Bearish Drift — High E, Bearish S, Low A — Clean continental drift downward.
⬥ Bullish Overshoot — High E, Bullish S, High A — Overextended, fracture risk.
⬥ Bearish Overshoot — High E, Bearish S, High A — Oversold, rebound risk.
◍ Silent Loading — Low E, High A, Bullish S — Deep accumulation beneath quiet surface.
◍ Silent Unloading — Low E, High A, Bearish S — Distribution masked by stillness.
◍ Compression Zone — Low E, High A, Neutral S — Maximum pressure. Breakout imminent.
◌ Dead Zone — Low E, Low A, Neutral S — No tectonic activity. Stay out.
○ Undirected Tremor — High E, Neutral S — Seismic noise without direction.
○ Transitional — Mixed readings — Plates reorganizing. Wait for clarity.
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🔔 SEISMIC ALERTS (6 CONDITIONS)
🔺 Seismic Acceleration — RA crosses threshold. The plates are grinding.
⚡ Force Divergence — Energy and Control moving against each other. Internal conflict.
🔥 Absorption Climax — Saturated ground with high energy and strong skew. Fracture zone.
⟳ Plate Reversal — RA spike with rapid rotation. The snap is coming.
⏳ Formation Fatigue — Ancient regime with eroding stability. End of geological era.
🔻 Fracture Alert — SPI above 60%. Silent crack detected underground.
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🎯 READING THE GROUND
For riding trends:
▲ or ▼ Drift + 🧱 Solid stability + ◇ No fractures + 🏛️ Established formation.
The ground beneath this trend is granite. Ride it.
For catching breaks:
⏳ Ancient formation + ↓ Eroding stability + 🔻 Rising fracture index + ⬥ Overshoot state.
When SPI crosses 60% — Internal Fracture confirms it. This is what RSI and MACD cannot feel underground.
For spotting hidden accumulation:
Low E + High A + S leaning one way = tectonic loading. The quiet surface hides massive positioning beneath. Precision entry zones.
For avoiding dead ground:
◌ Dead Zone or ○ Transitional + 🌪 Weak stability + 🌱 Fresh formation = no geological basis for a trade. Wait.
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⚙️ SETTINGS
🌐 Language — Arabic or English
⚙️ Structural — Core tectonic parameters (windows, smoothing, normalization)
⚡ Alerts — Thresholds for all 6 seismic conditions
📊 Quant — 12 hidden outputs for strategy integration
🎨 Visual — Colors, opacity, plate vectors, zones, fracture heatmap on/off
📋 Command Center — Full/Simple, position, size, border color
No repainting. No future data. Purely causal. Performance optimized. 12 quant outputs for automated systems.
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Tectonic does not predict where the market goes. It tells you what the ground is made of, how long it has been holding, and where the cracks are forming. The rest is your decision.
◈ Tectonic — هندسة حالة السوق ◈
الأرض تحت الشارت ليست صلبة. تتحرك. تتشقق. تبني ضغطاً لأسابيع — ثم تنكسر في ثوانٍ.
Tectonic لا يراقب السعر. يستمع إلى الأرض تحته.
كل سوق يقف على طبقات غير مرئية من الطاقة والسيطرة والامتصاص. عندما تتوازى هذه الطبقات، الاتجاه يسير بسلاسة. عندما تتباعد، السطح يصمد — لكن خطوط الصدع تنتشر بصمت في العمق. ثم يأتي الانكسار.
Tectonic يقرأ هذا. كل شمعة، يجيب على ثلاثة أسئلة:
→ ما الحالة البنيوية الحالية؟
→ هل تستطيع الصمود؟
→ أين تتشكّل خطوط الصدع؟
هذا ليس مؤشراً. هذا جهاز رصد زلازل لبنية السوق.
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🔬 الطبقات التكتونية الثلاث
أغلب المؤشرات ترى طبقة واحدة — السعر. Tectonic يرى ثلاثاً:
⚡ الطاقة (E)
القوة الخام التي تحرّك السوق. تُقاس بحجم معدل التغيّر، مُطبَّع عبر الترتيب المئوي. طاقة عالية تعني أن الأرض تتحرك بقناعة. طاقة منخفضة تعني أن السطح هادئ — لكن الهدوء لا يعني الأمان.
⚖️ السيطرة (S)
من يملك الزخم — المشترون أم البائعون؟ يستخدم تحليل نوافذ غير متماثل لكشف متى يتحوّل ميزان القوى بين الأيدي — غالباً قبل أن يُظهره السعر. فوق 60% سيطرة مشترين. تحت 40% سيطرة بائعين. قرب 50% خط صدع مُتنازع عليه.
🧲 الامتصاص (A)
كم ضغط تمتصه الأرض دون أن تُطلقه؟ هذه الطبقة التي لا يراها أغلب المتداولين. امتصاص عالٍ أثناء اتجاه يعني أن الصخر مشبع — لا يحتمل المزيد، الكسر وشيك. امتصاص عالٍ أثناء نطاق يعني أن الضغط يتراكم — الانفجار سيكون عنيفاً. معامل لامبدا يقرأ الامتصاص بشكل مختلف في الاتجاهات مقابل النطاقات.
هذه الثلاث تشكّل الحقل التكتوني. ليست حركة سعر. ليست أنماط شموع. القوى الفعلية التي تتحرك تحت الشارت.
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🧬 الميل البنيوي (α)
تحت ضوضاء الشموع الفردية، أي اتجاه تميل القارة؟
ألفا يقيس الاختلال المستمر بين الزخم الصاعد والهابط عبر نافذة بنيوية طويلة. فكّر فيه كميل جيولوجي — الانحياز الاتجاهي العميق الذي ينجو من الاضطرابات اليومية.
⦿ إيجابي قوي — الأساس يميل صعوداً
◉ معتدل — ميل اتجاهي خفيف
◎ قرب الصفر — أرض مسطحة، لا انحياز بنيوي
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🔺 التسارع الزلزالي (RA)
الهزّات تتزايد. شيء ما على وشك التحوّل.
RA يقيس سرعة تحرّك الحقل التكتوني بأكمله — الطاقة والسيطرة والامتصاص معاً:
RA = percentile_rank( |delta E| + |delta S| + |delta A| )
RA منخفض يعني هدوء جيولوجي. RA مرتفع يعني نشاط زلزالي — الصفائح تحتك. لا يخبرك إلى أين سيكون الانكسار. يخبرك أن الانكسار قادم.
هذا ما يسمح لـ Tectonic بكشف تحوّلات النظام قبل أن تظهر على السطح.
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◆ دوران الصفائح (θ, Δθ)
الصفائح التكتونية لا تدفع فقط — تدور.
Tectonic يُسقط العلاقة بين تغيّرات الطاقة والسيطرة على حقل دائري:
theta = atan2(delta S, delta E)
أربع مراحل دوران. أربعة ألوان. أربعة معانٍ:
🟠 مرحلة الدفع (0 إلى 45 و 315 إلى 360 درجة)
الصفائح تدفع بقوة في اتجاه واحد. الطاقة ترتفع، السيطرة محسومة. هذه مرحلة التسارع — الزخم يبني بقوة واضحة.
🟢 مرحلة التحويل (45 إلى 135 درجة)
الميزان يتحوّل. صفيحة تغوص تحت أخرى. القوة تنتقل من المشترين إلى البائعين أو العكس. السطح لم يتشقق بعد — لكن نقطة الضغط تتحرك.
🔵 مرحلة الهبوط (135 إلى 225 درجة)
القوة الدافعة تتلاشى. الصفيحة القديمة ما زالت في مكانها لكن لا طاقة لديها. هذا تآكل بنيوي — الاتجاه يغرق، لا ينكسر.
🔴 مرحلة الانهيار (225 إلى 315 درجة)
لا صفيحة تصمد. فوضى بنيوية. لا قناعة من أي طرف. هنا تعيش الإشارات الكاذبة — وهنا يولد النظام التالي من الركام.
عندما يتسارع الدوران بسرعة (|delta theta| مرتفع)، يُطلق Tectonic تحذير انعكاس صفائحي ⟳ — أوضح إنذار بأن الصفائح على وشك الانكسار.
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🧱 الاستقرار التكيّفي
هل الأرض صلبة — أم تقف على خط صدع؟
الاستقرار يجمع ثلاث قوى مزعزعة في قراءة واحدة:
stabilityBase = 1 - (RA x 0.4 + |delta theta| / pi x 0.4 + A x 0.2)
لكن القراءة بلا سياق لا معنى لها. استقرار 70% على نظام عمره 3 شموع هو رمل. نفس 70% بعد 50 شمعة من الاستمرارية هو صخر. لذلك Tectonic يُدرّجه:
stability = stabilityBase x (0.5 + maturity x 0.5)
التشكّلات الحديثة تحصل على نصف الأهلية. التشكّلات القديمة تحصل على كامل الأهلية. هذا تفكير جيولوجي — الصخر القديم أقوى من الرواسب الطازجة.
لاحظ: الامتصاص عامل ضغط خفي. تشكّل ناضج مع امتصاص عالٍ يبدو صلباً لكنه مشبع فعلياً. Tectonic يكشف هذا. المؤشرات التقليدية ترى سوقاً مستقراً. Tectonic يرى سداً على وشك الانهيار.
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⏳ ذاكرة التشكّل
كم عمر هذا التشكّل الجيولوجي؟ وهل يتقادم إلى صخر صوّاني — أم يتفتت إلى غبار؟
ساعتان مستقلتان:
عمر النظام — كم شمعة استمرت الحالة الحالية.
عمر الصفيحة — كم شمعة بقيت المرحلة الدورانية في نفس الربع.
عندما يكون كلاهما قديماً معاً، البنية متماسكة. عندما يتباعدان — نظام مستقر لكن صفائح تدور بجنون — السطح يبدو هادئاً لكن الشقوق تنتشر تحت الأرض.
تصنيف التشكّل:
🌱 أقل من 5 شموع — طازج (غير مُثبت، هش)
📈 5 إلى 20 شمعة — يتشكّل (يكتسب كثافة)
🏛️ 20 إلى 50 شمعة — مستقر (موثوق، يتحمّل الأحمال)
⏳ أكثر من 50 شمعة — قديم (قوي لكن هش تحت ضغط جديد)
اتجاه الاستقرار يُظهر هل التشكّل يتصلّب ↑ أو يصمد → أو يتآكل ↓.
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🔻 مؤشر الانكسار (SPI)
هذا هو سبب وجود Tectonic. كل شيء آخر يُبنى لهذه اللحظة.
phaseFrag = 1 - min(phaseDuration / regimeDuration, 1)
SPI = regimeMaturity x phaseFrag x (1 - stability)
مؤشر الانكسار يكشف الشقوق الصامتة. تخيّل هذا المشهد:
اتجاه صاعد صمد 60 شمعة. السعر يبدو قوياً. RSI يبدو صحياً. MACD يبدو جيداً. كل مؤشر تقليدي يقول استمر.
لكن تحت الأرض — الصفائح تدور بجنون داخل نظام مستقر. الاستقرار ينخفض شمعة بعد شمعة. التشكّل وقف طويلاً حتى أصبح هشاً.
مؤشر الانكسار يرى هذا. يرتفع بهدوء. عند 35% — شقوق شعرية. عند 60% — التوقع يتحوّل إلى انكسار داخلي. ثم يأتي الكسر — سريع، نظيف، مدمّر. غير مرئي لكل من يراقب السطح.
خريطة الانكسار الحرارية ترسم هذا مباشرة على الشارت. لا شيء مرئي عندما يكون الضغط منخفضاً. وهج كهرماني خافت مع تزايد الإجهاد. أحمر عميق مع وصول خط الصدع إلى الكتلة الحرجة. تشعر بالزلزال قبل أن تتحرك الأرض.
◇ أقل من 35% — أرض مستقرة. التشكّل سليم.
⚠️ 35% إلى 60% — إجهاد يتراكم. شقوق دقيقة تتشكّل.
🔻 فوق 60% — حرج. الانكسار وشيك.
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📋 مركز القيادة
وضعان لعقليتين مختلفتين:
الوضع الكامل (18 صفاً) — للجيولوجي الذي يريد كل طبقة مرئية:
الميل البنيوي مع الانحياز، E S A مع النسبة والمقياس، التسارع الزلزالي، تفاصيل آخر إشارة (لون الصفيحة، الاتجاه، حالة الانعكاس، العمر)، النظام الحالي، ذاكرة التشكّل مع العمر والنضج واتجاه الاستقرار، الاستقرار التكيّفي مع المقياس، عمر الصفيحة مع اسم المرحلة، مؤشر الانكسار مع المقياس، والتوقع التكتوني.
الوضع البسيط (5 صفوف) — للمتداول الذي يحتاج نظرة واحدة:
النظام مع الاتجاه وعمر التشكّل، الاستقرار مع تحذير الانكسار، E S A مختصرة، والتوقع.
التبديل في أي وقت من الإعدادات تحت الوضع.
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📊 الحالات التكتونية
▲ انجراف صعودي — E عالي، S صعودي، A منخفض — انجراف قاري نظيف للأعلى.
▼ انجراف هبوطي — E عالي، S هبوطي، A منخفض — انجراف قاري نظيف للأسفل.
⬥ تجاوز صعودي — E عالي، S صعودي، A عالي — تمدد مفرط، خطر انكسار.
⬥ تجاوز هبوطي — E عالي، S هبوطي، A عالي — بيع مفرط، خطر ارتداد.
◍ تحميل صامت — E منخفض، A عالي، S صعودي — تراكم عميق تحت سطح هادئ.
◍ تفريغ صامت — E منخفض، A عالي، S هبوطي — توزيع مُقنّع بالسكون.
◍ منطقة ضغط — E منخفض، A عالي، S محايد — ضغط أقصى. اختراق وشيك.
◌ منطقة ميتة — E منخفض، A منخفض، S محايد — لا نشاط تكتوني. ابتعد.
○ هزّة بلا اتجاه — E عالي، S محايد — ضوضاء زلزالية بلا اتجاه.
○ انتقالي — قراءات مختلطة — الصفائح تعيد ترتيبها. انتظر الوضوح.
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🔔 التنبيهات الزلزالية (6 شروط)
🔺 تسارع زلزالي — RA يتجاوز العتبة. الصفائح تحتك.
⚡ تباين القوى — الطاقة والسيطرة تتحركان ضد بعضهما. صراع داخلي.
🔥 ذروة امتصاص — أرض مشبعة مع طاقة عالية وانحراف قوي. منطقة انكسار.
⟳ انعكاس صفائحي — ارتفاع RA مع دوران سريع. الانكسار قادم.
⏳ إرهاق تشكّل — نظام قديم مع استقرار يتآكل. نهاية حقبة جيولوجية.
🔻 تنبيه انكسار — SPI فوق 60%. شق صامت مُكتشف تحت الأرض.
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🎯 قراءة الأرض
لركوب الاتجاهات:
▲ أو ▼ انجراف + 🧱 استقرار صلب + ◇ لا انكسارات + 🏛️ تشكّل مستقر.
الأرض تحت هذا الاتجاه صخر صوّاني. اركبه.
لاصطياد الانكسارات:
⏳ تشكّل قديم + ↓ استقرار يتآكل + 🔻 مؤشر انكسار يرتفع + ⬥ حالة تجاوز.
عندما يتجاوز SPI الـ 60% — الانكسار الداخلي يؤكده. هذا ما لا يستطيع RSI و MACD الإحساس به تحت الأرض.
لاكتشاف التراكم الخفي:
E منخفض + A عالي + S يميل لاتجاه = تحميل تكتوني. السطح الهادئ يخفي تموضعاً ضخماً في العمق. مناطق دخول دقيقة.
لتجنب الأرض الميتة:
◌ منطقة ميتة أو ○ انتقالي + 🌪 استقرار ضعيف + 🌱 تشكّل طازج = لا أساس جيولوجي للصفقة. انتظر.
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⚙️ الإعدادات
🌐 اللغة — عربي أو إنجليزي
⚙️ بنيوي — معاملات تكتونية أساسية (النوافذ، التنعيم، التطبيع)
⚡ التنبيهات — عتبات الشروط الزلزالية الستة
📊 الكمّي — 12 مخرج مخفي لربط الاستراتيجيات
🎨 بصري — الألوان، الشفافية، أسهم الصفائح، المناطق، خريطة الانكسار الحرارية
📋 مركز القيادة — كامل/بسيط، الموضع، الحجم، لون الإطار
لا إعادة رسم. لا بيانات مستقبلية. سببي بالكامل. أداء محسّن. 12 مخرج كمّي للأنظمة الآلية.
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Tectonic لا يتنبأ أين يذهب السوق. يخبرك ممّا تتكوّن الأرض، كم صمدت، وأين تتشكّل الشقوق. الباقي قرارك. Indicator
Wolfe Wave Pattern [UAlgo]Wolfe Wave Pattern is a pivot based pattern recognition indicator that scans price structure for a five point Wolfe Wave sequence and automatically draws the pattern on the chart once a valid setup is confirmed. The script works directly on price ( overlay=true ) and is built for visual analysis, giving traders a clear geometric representation of bullish and bearish Wolfe Wave formations with point labels, channel references, and a projected EPA target line.
This implementation uses confirmed swing pivots from PulseWire pivot functions as its structural foundation. Every new confirmed pivot is stored, and the script evaluates the most recent five alternating pivots for Wolfe Wave conditions. Instead of trying to detect every possible variation, it applies a practical and consistent ruleset based on swing sequencing, relative highs and lows, convergence of channel lines, and point 5 overshoot behavior beyond the 1 to 3 guide line.
When a valid pattern is found, the script draws the core wave legs (1 to 2, 2 to 3, 3 to 4, 4 to 5), a 2 to 4 channel reference, a 1 to 3 sweet zone guide, and an extended EPA line from 1 to 4 into the future. It also marks the pivot points with labels and triggers an alert message at detection time.
This makes the tool useful for discretionary traders who want a structured way to monitor Wolfe Wave geometry without manually drawing every candidate pattern.
🔹 Features
🔸 1) Pivot Based Wolfe Wave Detection
The script uses ta.pivothigh() and ta.pivotlow() with user configurable left and right bars to build a swing structure map. Each pivot is stored as a custom PivotPoint object containing:
Index of the pivot bar
Pivot price
Pivot type (high or low)
This gives the pattern engine a clean sequence of confirmed turning points rather than raw candle noise.
🔸 2) Automatic Five Point Pattern Recognition
On each newly confirmed pivot, the script checks the most recent five pivots and validates whether they form an alternating sequence suitable for a Wolfe Wave candidate. Only alternating high low high low high or low high low high low structures are considered.
This is an important filter because Wolfe Waves are geometric swing patterns and require clear alternation in pivot direction.
🔸 3) Bullish Wolfe Wave Detection Logic
The bullish model looks for a low high low high low sequence and applies structural and geometric checks, including:
Point 3 below Point 1
Point 4 below Point 2
Point 5 overshooting below the projected 1 to 3 line
Converging channel behavior through slope comparison of 1 to 3 and 2 to 4
This produces a clean descending wedge style candidate that matches the intended bullish Wolfe Wave concept in this implementation.
🔸 4) Bearish Wolfe Wave Detection Logic
The bearish model looks for a high low high low high sequence and applies the inverse logic:
Point 3 above Point 1
Point 4 above Point 2
Point 5 overshooting above the projected 1 to 3 line
Converging channel behavior through slope comparison of 1 to 3 and 2 to 4
This creates a rising wedge style candidate for bearish Wolfe Wave detection.
🔸 5) Full Pattern Drawing on Chart
Once detected, the script draws the pattern directly on price using line objects:
Wave legs 1 to 2, 2 to 3, 3 to 4, and 4 to 5
A 2 to 4 channel reference line
A 1 to 3 sweet zone guide line
An EPA projection line extended from 1 to 4 into future bars
This helps traders quickly inspect geometry and projected target direction without manual plotting.
🔸 6) Point Labels and Pattern Name Display
The indicator labels all five pivot points and positions the labels above or below price depending on pattern direction. This improves readability and makes it easy to verify the sequence visually.
For bullish patterns, low points are labeled below bars and high points above bars. For bearish patterns, the logic is inverted.
🔸 7) EPA Target Projection
The script draws an extended EPA line based on Point 1 and Point 4, projecting it beyond Point 5 to create a visual target path. This offers a practical reference for post detection expectation analysis.
The projection length is proportional to the 1 to 4 horizontal distance, which keeps the target line visually consistent with the pattern scale.
🔸 8) Visual Customization Inputs
Users can customize:
Bullish pattern color
Bearish pattern color
Line width
The script also includes a line style input and line style helper mapping. In the current implementation, core pattern segments are drawn with fixed style choices for visual consistency, while supporting lines use dedicated dashed and arrow styles.
🔸 9) Alert on Detection
When a new bullish or bearish Wolfe Wave is confirmed, the script triggers an alert message at bar close frequency. This allows traders to monitor multiple symbols or timeframes without constantly watching the chart.
🔸 10) Structured Object Design for Maintainability
The script uses custom types for both pivots and patterns:
PivotPoint for swing points
WolfeWave for the full detected pattern including lines, labels, EPA line, and sweet zone line
This object based design keeps the code organized and easier to extend in future versions.
🔹 Calculations
1) Pivot Detection and Storage
The script identifies confirmed swing highs and lows using user defined left and right pivot lengths:
float ph = ta.pivothigh(high, lenLeft, lenRight)
float pl = ta.pivotlow(low, lenLeft, lenRight)
When a pivot is confirmed, it is stored at the actual pivot bar index ( bar_index - lenRight ) because pivot confirmation happens after the right side bars are complete:
if not na(ph)
pivotArray.addPivot(bar_index - lenRight, ph, true)
if not na(pl)
pivotArray.addPivot(bar_index - lenRight, pl, false)
The pivot array is capped to a manageable size:
if pivots.size() > 100
pivots.shift()
2) Pattern Scan Trigger and Five Pivot Window
The pattern engine only runs when at least five pivots exist. It then reads the latest five pivots in order:
PivotPoint p5 = pivotArray.get(pivotArray.size() - 1)
PivotPoint p4 = pivotArray.get(pivotArray.size() - 2)
PivotPoint p3 = pivotArray.get(pivotArray.size() - 3)
PivotPoint p2 = pivotArray.get(pivotArray.size() - 4)
PivotPoint p1 = pivotArray.get(pivotArray.size() - 5)
The check is gated so the recognition logic processes only when a new pivot has just been confirmed:
bool newPivotConfirmed = not na(ph) or not na(pl)
3) Alternation Check
Before applying Wolfe rules, the script requires the five pivots to alternate between highs and lows:
bool alternating = (p1.isHigh != p2.isHigh) and (p2.isHigh != p3.isHigh) and (p3.isHigh != p4.isHigh) and (p4.isHigh != p5.isHigh)
This prevents invalid sequences such as repeated highs or repeated lows from being treated as pattern candidates.
4) Slope and Projection Utilities
Two helper methods provide the geometric basis of the pattern logic:
Slope between two pivots:
method getSlope(PivotPoint pA, PivotPoint pB) =>
(pB.price - pA.price) / (pB.index - pA.index)
Projected price of a line at a target bar index:
method getProjectedPrice(PivotPoint pA, PivotPoint pB, int targetIndex) =>
float slope = (pB.price - pA.price) / (pB.index - pA.index)
pA.price + slope * (targetIndex - pA.index)
These methods are used for overshoot validation, convergence checks, and EPA target projection.
5) Bullish Wolfe Wave Detection Rules
The bullish pattern requires a pivot sequence of:
Point 1 low
Point 2 high
Point 3 low
Point 4 high
Point 5 low
In code, this is checked as:
if not p1.isHigh and p2.isHigh and not p3.isHigh and p4.isHigh and not p5.isHigh
Then the script applies structural conditions:
if p3.price < p1.price and p4.price < p2.price
This enforces a downward contracting structure.
Next, it checks Point 5 overshoot relative to the projected 1 to 3 line at the Point 5 index:
float proj13_at_5 = p1.getProjectedPrice(p3, p5.index)
if p5.price < proj13_at_5
Finally, it checks convergence using slope comparison:
float m13 = p1.getSlope(p3)
float m24 = p2.getSlope(p4)
if m24 < m13
detected := true
Interpretation:
For a bullish setup in this script, both 1 to 3 and 2 to 4 slopes are typically negative, and the 2 to 4 line must descend faster than the 1 to 3 line so the structure converges to the right.
6) Bearish Wolfe Wave Detection Rules
The bearish pattern requires a pivot sequence of:
Point 1 high
Point 2 low
Point 3 high
Point 4 low
Point 5 high
In code:
else if p1.isHigh and not p2.isHigh and p3.isHigh and not p4.isHigh and p5.isHigh
Structural conditions:
if p3.price > p1.price and p4.price > p2.price
This enforces an upward contracting structure.
Point 5 overshoot must be above the projected 1 to 3 line:
float proj13_at_5 = p1.getProjectedPrice(p3, p5.index)
if p5.price > proj13_at_5
Convergence is then checked using slope comparison:
float m13 = p1.getSlope(p3)
float m24 = p2.getSlope(p4)
if m24 > m13
detected := true
Interpretation:
For a bearish setup, both lines are typically rising, and the 2 to 4 line must rise faster than the 1 to 3 line so the wedge contracts to the right.
7) Sweet Zone Guide and Channel Reference
After detection, the script draws a sweet zone guide using the 1 to 3 geometry projected to the Point 5 index:
this.sweetZoneLine := line.new(
this.p1.index, this.p1.price,
this.p5.index, this.p1.getProjectedPrice(this.p3, this.p5.index),
color=color.new(c, 50), width=1, style=line.style_dashed)
It also draws a 2 to 4 reference line as a dashed channel boundary:
this.patternLines.push(line.new(this.p2.index, this.p2.price, this.p4.index, this.p4.price, color=color.new(c, 50), width=1, style=line.style_dashed))
Together, these lines visually frame the Wolfe Wave channel and the Point 5 overshoot area.
8) EPA Line Projection
The EPA line is projected from Point 1 to Point 4 and extended into the future. The horizontal projection length is based on the bar distance from Point 1 to Point 4:
int dist14 = this.p4.index - this.p1.index
int targetIdx = this.p5.index + dist14
float targetPrice = this.p1.getProjectedPrice(this.p4, targetIdx)
The EPA line is then drawn with an arrow style:
this.epaLine := line.new(this.p1.index, this.p1.price, targetIdx, targetPrice, color=color.yellow, width=2, style=line.style_arrow_right)
This provides a projected target path for the expected move after Point 5.
9) Label Placement Logic
The script places point labels above or below bars based on pattern direction so the labels remain readable and consistent with swing polarity.
For bullish patterns:
Points 1, 3, and 5 are placed below bars
Points 2 and 4 are placed above bars
For bearish patterns:
Points 1, 3, and 5 are placed above bars
Points 2 and 4 are placed below bars
This logic is encoded through direction dependent yloc assignment before creating labels.
10) Detection Object Construction and Drawing
Once a pattern is validated, the script creates a WolfeWave object and calls its draw method:
WolfeWave ww = WolfeWave.new(p1, p2, p3, p4, p5, isBull)
ww.draw()
The object stores the five pivots, direction, line arrays, label arrays, and special lines (EPA and sweet zone), which makes the implementation modular and easier to manage.
11) Alert Logic
After a bullish or bearish pattern is drawn, the script sends an alert message:
alert("Wolfe Wave " + (isBull ? "Bullish" : "Bearish") + " Detected", alert.freq_once_per_bar_close)
This allows users to automate notification workflows and review setups only when a complete pattern has been confirmed. Indicator
Adaptive Quasimodo + Confluence Engine - PhenLabs📊Quasimodo Pattern (QM) Detector - PhenLabs
Recognizing reversal patterns like the Quasimodo can be challenging and time-consuming, requiring a keen eye for specific market structures. Missing a key swing point or misinterpreting a retracement can lead to missed opportunities or false signals. This indicator automates the precise identification of Quasimodo patterns, providing clear, actionable signals directly on your chart, so you can focus on execution.
🚨OVERVIEW🚨
The Quasimodo Pattern (QM) Detector is an advanced, non-repainting indicator designed to automatically spot high-probability bullish and bearish Quasimodo reversal patterns. It integrates customizable swing point detection, confluence filters (Higher Timeframe trend and volume confirmation), and precise entry, stop-loss, and take-profit calculations directly from the pattern’s structure. Get automated alerts and a real-time dashboard to enhance your pattern-based trading strategy.
🔷 WHAT IS A QUASIMODO (QM) PATTERN?
The Quasimodo pattern is a powerful reversal formation characterized by a specific sequence of price action:
Bearish QM: A Higher High (HH) is followed by a Lower Low (LL), then a Higher High (HH), and finally a Lower Low (LL). The pattern suggests a reversal from an uptrend to a downtrend, often at the level of the previous Higher High.
Bullish QM: A Lower Low (LL) is followed by a Higher High (HH), then a Lower Low (LL), and finally a Higher High (HH). This suggests a reversal from a downtrend to an uptrend, often at the level of the previous Lower Low.
It’s a cousin to the Head & Shoulders pattern but with a distinct structure focused on specific swing points.
🔶 KEY FEATURES
Automated QM Detection: Accurately identifies both bullish and bearish Quasimodo patterns as they form on any timeframe.
Customizable Swing Points: Define how swing highs and lows are detected, choosing between using wick extremes or candle bodies.
Confluence Filters: Incorporates a Higher Timeframe (HTF) Trend filter to confirm pattern alignment using a non-repainting EMA, and a Volume Confirmation filter to validate patterns with significant volume spikes at key structural points.
Dynamic Trade Planning: Automatically calculates suggested Entry, Stop Loss, and Take Profit levels based on the detected QM structure and your desired Risk-to-Reward ratio.
Non-Repainting Logic: All detected patterns and signals are permanent and do not shift or disappear on subsequent bars.
Informative Dashboard: Provides a real-time summary of HTF trend, volume confirmation, and the last detected QM.
Visual Clarity: Plots QM lines, potential entry/SL/TP zones, and clear labels for pattern identification.
Alerts: Customizable alerts for new QM patterns and when price enters the suggested entry zone.
⚙️ SETTINGS GUIDE
Pattern Recognition: Adjust settings like Use Wick As Extremes (for swing points), Swing Lookback (how many bars to scan for swings), Min Head Height/Right Shoulder Depth Factor (magnitude requirements), Strict Higher/Lower High/Low (stricter swing definitions), and Max RSL/RSH Bars (time limit for right shoulder formation).
Trade Management: Configure Entry/SL/TP Offset % to fine-tune entry, stop-loss, and take-profit levels as a percentage buffer, and set your Desired Risk:Reward ratio for calculating Take Profit.
Confluence Filters: Enable or disable Use HTF Confirmation and Use Volume Confirmation . For HTF, set HTF Timeframe and EMA Length . For Volume, adjust Volume Lookback and Multiplier .
Visual Settings: Toggles are available for showing QM lines, entry/SL/TP zones, alerts, and dashboard position.
📈 TRADING WORKFLOW
Identify: Wait for a Bullish or Bearish QM pattern to be detected and labeled on your chart.
Confirm: Check the dashboard and pattern details. Ensure the HTF trend and Volume confirmation are aligned with the pattern’s direction (e.g., Bullish QM + Bullish HTF).
Enter: Wait for price to retest the suggested entry zone. The indicator plots these zones for you.
Manage: Use the automatically calculated Stop Loss and Take Profit levels, adjusting them as needed based on market context and your risk management strategy.
Alerts: Set up alerts to be notified immediately when a QM pattern is found or when price enters an entry zone.
⚠️ RISK DISCLAIMER
Trading involves substantial risk, and past performance is not indicative of future results. The Quasimodo Pattern Detector is a tool to assist in identifying potential trade setups but does not guarantee profitability. Always conduct your own analysis and implement proper risk management.
Does it repaint?
No. This indicator is coded with non-repainting logic. Once a pattern is confirmed and a signal is generated on a closed bar, it will remain on your chart permanently. The Higher Timeframe trend filter also uses a non-repainting method. Indicator
TX Ultra Pulse TWH## Overview
TX Ultra Pulse TWH is a normalized momentum oscillator designed to visualize trend strength and identify potential reversal points. Unlike standard oscillators that use fixed ranges (0-100), this script normalizes its output into a standardized histogram (typically fluctuating between -1.5 and +1.5), making it easier to compare volatility across different assets.
## How It Works (The Logic)
The indicator allows users to switch between 4 different calculation "Engines". Each engine processes price data differently but outputs a normalized result:
1. Composite Mode (Default & Recommended)
This mode creates a "consensus" signal by blending three classic momentum indicators to filter out noise.
Logic: It calculates the 14-period RSI, 14-period Stochastic, and 20-period CCI.
Normalization: RSI and Stochastic are centered around zero (subtracting 50). CCI is divided by 150 to match the scale.
Weighting: The formula uses a weighted average: (RSI + (Stoch * 2) + CCI) / 3. The Stochastic component is given double weight to prioritize reaction to recent price closes.
Result: A smoother oscillator that reacts to overbought/oversold conditions with less "whipsaw" than a raw RSI.
2. Deviation Mode
Logic: Calculates the percentage distance between the Close price and a Moving Average (default 20 SMA).
Scaling: The result is normalized using Standard Deviation (Z-Score concept) to fit the histogram scale.
Use Case: Best for spotting mean-reversion opportunities when price extends too far from its baseline.
3. Momentum Mode
Logic: Pure Rate-of-Change (ROC). It measures the percentage change between current close and close n periods ago.
Use Case: Ideal for identifying pure trend velocity without the smoothing lag of complex averages.
4. RS Index Mode
Logic: Comparative Relative Strength. It compares the performance of the current asset against a user-defined benchmark (e.g., SPY, BTC, or IDX:COMPOSITE) over a lookback period.
Formula: (Asset % Change - Benchmark % Change). Positive values indicate the asset is outperforming the market.
## Features & Settings
Noise Filter: A built-in EMA smoothing layer (default 15) is applied to the final calculation to reduce visual noise.
Color Grading:
Green: Positive Momentum (Bullish).
Red/Orange: Negative Momentum (Bearish).
Color Intensity: Brighter colors indicate accelerating momentum, while darker/faded colors indicate deceleration (divergence).
Dashboard: Displays the current real-time values, trend direction, and signal status directly on the chart.
## How to Use
Trend Confirmation: Use the histogram color to confirm the trend direction. Do not go Long if the histogram is Red.
Zero Cross: A crossover above 0 indicates a shift to bullish momentum. A cross below 0 indicates bearish momentum.
Divergence: If price makes a Higher High but the Pulse Histogram makes a Lower High, this indicates momentum exhaustion (Bearish Divergence).
## Disclaimer
This script is a technical analysis tool intended for educational purposes. It does not guarantee profits. Past performance is not indicative of future results. Indicator
ZigZag Fibo Cluster (PRZ)This indicator is designed to identify high-probability Potential Reversal Zones (PRZ) by combining Multi-Timeframe (MTF) analysis with Fibonacci clusters. It focuses on filtering out market noise to find mathematically validated support and resistance levels, making it highly effective for intraday trading and sniper entries.
Core Logic & Key Features:
Dual-Layer ZigZag Architecture: The system simultaneously tracks two different ZigZag structures on the chart. It calculates a "Major" wave (default 10-5) for higher timeframes (1D, 4H, 1H) and a "Minor" wave (default 6-3) for the active lower timeframe (e.g., 20m).
Fibonacci Cluster (Kissing) Detector: Fibonacci retracements and extensions from different timeframes rarely align perfectly. This indicator continuously cross-references the active Fibo levels from the Major and Minor structures to find algorithmic overlaps.
Strict 0.1% Precision Tolerance: When a Major Fibonacci level and a Minor Fibonacci level converge within a strict 0.1% price margin, the system validates this as a "Cluster" and plots a precise "PRZ ±0.1%" label on the chart.
Visual Clarity & Chart Cleanliness: It prevents chart clutter by hiding hundreds of irrelevant Fibonacci lines. It only prints labels where the 0.1% tolerance condition is met—meaning both the macro and micro structures agree on the reversal point. Historical wave references are kept as subtle dotted lines.
Dynamic Customization: All ZigZag deviation parameters (Left/Right bars) and extended Fibonacci levels (1.272, 1.618, -0.618, etc.) can be fully customized via the settings menu to adapt to different asset volatilities.
How to Use:
When the "PRZ ±0.1%" label appears, it indicates that the current price action has reached both its macro and micro algorithmic targets. These specific zones provide asymmetric risk/reward opportunities, allowing traders to plan trend reversals, define take-profit areas, or execute counter-trend trades with extremely tight stop-loss margins. Indicator
Indicator
Ciera Supply and Demand xATR Exhaustion Meter (Zones) xATR Exhaustion Meter (Zones)
xATR Exhaustion Meter is a volatility-aware decision tool designed to help traders evaluate whether price is arriving at a supply or demand zone with exhaustion or momentum.
Instead of guessing whether a zone will react or break, this indicator measures how far price has traveled relative to current market volatility using ATR (Average True Range) and analyzes the quality of price arrival.
The result is a simple, real-time exhaustion assessment displayed in a clean table interface.
---
🔍 What the Indicator Does
The indicator evaluates three core components when price interacts with a manually defined supply or demand zone:
1. Volatility-Adjusted Distance (xATR)
Measures how far price has moved into a zone relative to ATR:
Large xATR approach → move may be extended
Small xATR approach → move may still have energy
This normalizes movement across all timeframes and market conditions.
---
2. Arrival Momentum Analysis
The indicator evaluates candle body strength compared to recent averages and optionally confirms momentum direction using RSI slope.
This helps determine whether price is:
accelerating into a zone, or
losing momentum before arrival.
---
3. Exhaustion Classification
When price touches a zone, the meter classifies market condition as:
EXHAUSTED (react) — move may be stretched; reaction more likely
ENERGETIC (break) — strong arrival momentum; continuation more likely
NEUTRAL — confirmation required
---
📊 Features
Works on all markets and timeframes
ATR selectable from Chart, 1H, 4H, or Daily timeframe
Manual Supply & Demand zone inputs
Wick or Close-based zone detection
Volatility-normalized xATR measurements
Clean table-only interface (no chart clutter)
Optional alerts for exhaustion or energetic arrivals
Zone visualization toggle
---
🧠 How to Use
1. Mark your supply and demand zones manually.
2. Enter zone prices into the indicator inputs.
3. Watch the Exhaustion Meter when price reaches the zone.
General interpretation:
EXHAUSTED → look for confirmation of reaction/reversal.
ENERGETIC → expect higher probability of continuation or breakout.
NEUTRAL → wait for structure confirmation.
This tool is intended to assist decision-making, not replace price action analysis.
---
⚠️ Notes
Zones are manually defined by the trader.
The indicator evaluates arrival conditions, not future direction.
Best used alongside structure, liquidity, or order flow analysis.
---
🎯 Designed For
Traders using:
Supply & Demand
Market Structure
Smart Money Concepts (SMC)
Price Action trading
Volatility-based analysis
Indicator
Indicator
Gann-Fibonacci Swing Toolkit [BigBeluga]🔵 OVERVIEW
Gann–Fibonacci Swing Toolkit is an advanced swing-based projection tool that combines classic Gann geometry with Fibonacci ratios.
The indicator automatically detects market swings, anchors them to the most recent structure, and dynamically plots either Gann Fans or Gann Boxes to visualize price–time relationships, trend angles, retracement zones, and expansion targets.
This toolkit is designed to help traders understand not only where price may react, but also how fast it should move relative to time.
🔵 HISTORICAL BACKGROUND
The foundation of this toolkit comes from two of the most influential schools of market geometry:
W.D. Gann (early 1900s) introduced the idea that markets move according to geometric and mathematical laws, where price and time must stay in balance . His work emphasized angles (such as 1×1, 1×2, 1×3) that define how much price should advance or decline per unit of time.
Fibonacci ratios , derived from the Fibonacci sequence and popularized in trading decades later, describe natural proportional relationships observed across markets, especially during corrections and expansions.
Modern technical analysis merges these ideas by applying Fibonacci ratios to Gann’s price–time framework, creating tools that measure both distance (price) and duration (time) .
The Gann–Fibonacci Swing Toolkit follows this combined philosophy by grounding all projections in real swing structure rather than static or manually drawn anchors.
🔵 CORE CONCEPT
Swing-Based Anchoring — All calculations start from confirmed swing highs and lows detected via a rolling highest/lowest lookback.
Directional Context — The tool automatically determines bullish or bearish structure and adapts all projections accordingly.
Price–Time Geometry — Gann logic is applied by projecting price movement relative to elapsed bars, not just price distance.
🔵 KEY FEATURES
SWING DETECTION LOGIC
A swing high is confirmed when price forms a local maximum and then fails to extend higher.
A swing low is confirmed when price forms a local minimum and then fails to extend lower.
The most recent completed swing becomes the anchor point for all Gann and Fibonacci calculations.
Optional ZigZag lines visually connect completed swings for structural clarity.
GANN FAN MODE
When Fibonacci Type = Fan , the indicator plots dynamic Gann fan angles from the swing anchor.
Fan Ratios — Each fan line represents a 1/x (1/1, 1/2, 1/3, etc.), defining how much price should move per unit of time.
Trend-Aware Projection
- Bullish fans project upward from swing lows.
- Bearish fans project downward from swing highs.
Fan Fill Zones — Optional shaded regions between fan levels highlight price compression and expansion areas.
GANN BOX (FIBONACCI BOX) MODE
When Fibonacci Type = Box , the indicator builds a Gann Box using Fibonacci retracement and time ratios.
Horizontal Levels — Fibonacci price retracement levels (0.236, 0.382, 0.5, 0.618, 0.786) are projected from the swing range.
Vertical Levels — Fibonacci time divisions are applied across the swing duration to estimate timing of reactions.
Inverse Mode — Flips retracement logic to project inverted expansions instead of standard pullbacks.
OTE Zone — Optional Optimal Trade Entry zone highlights the premium/discount retracement area.
Dual-Axis Structure — Combines price and time into a single geometric framework instead of treating them separately.
MAIN FRAME LOGIC
A dynamic frame is drawn between the swing anchor and current bar, scaled by trend slope.
The frame visually represents the dominant trend channel derived from swing geometry.
VISUAL ELEMENTS
Swing anchor labels mark the exact price and bar index used for calculations.
Color-coded bullish and bearish swings improve structural readability.
Labels on fan and box levels display their exact Fibonacci ratios.
🔵 HOW TO USE
Use Gann Fans to trade dynamic trend support and resistance that evolves with time.
Use Gann Boxes to identify high-probability retracement zones and timing windows.
Combine fan angles with horizontal box levels for confluence-based entries.
Disable ZigZag if you want a cleaner chart focused only on projections.
🔵 CONCLUSION
Gann–Fibonacci Swing Toolkit is a geometry-driven market structure tool that goes beyond static Fibonacci levels.
By uniting Gann’s price–time balance with Fibonacci proportionality and anchoring everything to real swing structure, the indicator provides a deeper framework for understanding trend behavior, corrective depth, and future reaction zones — all derived directly from price action itself. Indicator
ACTApex Trend Consensus (ATC)
Overview
Apex Trend Consensus is a multi-indicator voting system designed for swing trading on trending assets, particularly crypto. Instead of relying on a single indicator, ATC combines 10 independent trend indicators into a unified consensus signal — reducing noise and false signals that plague single-indicator strategies.
How It Works
Each of the 10 indicators independently votes bullish (+1), bearish (-1), or neutral (0) on every bar. The votes are tallied into a Bull Score and Bear Score (max 10 each), and the difference determines the overall trend signal.
The 10 Indicators
Supertrend — ATR-based trend follower that adapts to volatility
ALMA Smooth — Arnaud Legoux Moving Average with reduced lag and smoothing
CTI — Correlation Trend Indicator measuring price momentum vs deviation
Sebastine Trend Catcher — Fast/slow EMA crossover system
Gunxo Trend Sniper — Dual EMA price position filter
DEMA DMI — Double EMA combined with Directional Movement Index
MM Momentum — Price position within recent range + EMA confirmation
DMI Oscillator — Smoothed directional movement differential
Trend Oscillator — Fast/slow EMA ratio measuring trend strength
Stochastic Filter — Normalized stochastic with threshold confirmation
Signal System
The score difference is classified into four levels:
DifferenceSignalAction> +3STRONG BULLBUY / HOLD+1 to +3WEAK BULLCAUTION-1 to -3WEAK BEARREDUCE< -3STRONG BEARSELL / EXIT
Signals require 2 consecutive bars of confirmation before triggering, which filters out short-lived whipsaws and keeps you in the trend longer.
Key Features
Consensus-based — No single indicator can dominate the signal. All 10 carry equal weight.
Trend persistence — Once confirmed, the trend signal holds until a new opposing confirmation appears. No flip-flopping.
Bar-close execution — Trades are processed on bar close, ensuring signals are fully confirmed before entry or exit.
Built-in dashboard — Visual overlay showing Bull Score, Bear Score, difference, current signal, and recommended action (available as a separate companion indicator).
Recommended Usage
Timeframe: Daily (1D) for swing trading
Assets: Crypto pairs, particularly BTC/USD and major alts
Style: Trend following — designed to catch big moves and stay in them
Approach: Long-only. Enters on bullish consensus, exits on bearish consensus.
Important Notes
This is a trend-following system — it will not catch exact tops or bottoms. It prioritizes staying in profitable trends over perfect timing.
Win rate is typically around 30-40%, but profitable trades significantly outweigh losing ones (profit factor ~2.4).
Best suited for assets with strong trending behavior. Less effective in choppy, range-bound markets.
Past performance does not guarantee future results. Always use proper risk management. Strategy
Elliott Wave (Experimental) [UAlgo]Elliott Wave (Experimental) is an automated swing based Elliott Wave scanner that attempts to classify recent market structure into common motive and corrective wave patterns. The script first converts price into a cleaned swing sequence using pivot confirmation and a minimum swing percentage filter. It then runs a two pass detection process that prioritizes five wave patterns first and fills remaining gaps with three wave corrective structures. Each detected pattern is validated with a rule engine, assigned a confidence score using Fibonacci ratio proximity, and rendered on the chart with wave labels, wave lines, optional channels, and optional Fibonacci projection targets.
This indicator is labeled experimental by design. Elliott Wave interpretation is inherently probabilistic and can vary between analysts, so the script focuses on transparent, rule driven validation and a confidence model that helps you judge the quality of each detected structure. Instead of presenting a single rigid count, it can render multiple detected patterns in the swing history and then highlights the latest one in a dashboard with direction, confidence, rule pass ratio, and a next target estimate.
🔹 Features
1) Swing Engine with Pivot Confirmation and Minimum Move Filter
The foundation of the scanner is a zigzag style swing engine. Swings are built from pivot highs and pivot lows confirmed by a configurable lookback. A Min Swing percent filter ensures that only meaningful moves are added as new swings. When consecutive pivots of the same type appear, the engine keeps only the better extreme, which helps reduce noise.
This creates a stable swing sequence that becomes the input for all wave pattern validators.
2) Multiple Pattern Families Supported
The scanner supports a wide set of Elliott structures, each enabled or disabled by inputs:
Impulse 1 2 3 4 5
Diagonal leading or ending with contracting or expanding classification
Zigzag ABC with a 5 3 5 style model
Flat ABC with regular expanded and running classification
Triangle ABCDE with contracting or expanding detection
Combination WXY for double three style sequences
Because patterns can overlap, the script uses a two pass orchestration that gives five wave structures priority, then looks for three wave structures in unused swing segments.
3) Rule Engine with Transparent Results
Each validator returns a WavePattern object that contains:
Wave list with labeled segments
A pattern type tag
Direction bullish or bearish
Validation state
Confidence score
Detailed rule results with pass and fail status and descriptive text
Rules implement common academic guidelines, such as Wave 2 not exceeding Wave 1 origin, Wave 3 not being the shortest, diagonal overlap behavior, and triangle containment conditions.
A relaxed overlap option can be enabled to allow minor Wave 4 overlap into Wave 1 territory when analyzing leveraged or futures markets where strict cash market rules may be less reliable.
4) Fibonacci Based Confidence Scoring
When a pattern passes its core rules, it receives a confidence score based on how close key measured ratios are to common Fibonacci ideals. The score is designed to reward clean proportionality and alternation behavior, while penalizing overlap or weak impulse characteristics.
Confidence is shown in the dashboard and is also mapped to a color for fast interpretation.
5) Rich Chart Rendering with Optional Components
Detected patterns can render several layers of visuals:
Wave lines connecting swing points
Wave labels placed above highs and below lows
Optional wave channel for motive patterns
Optional Fibonacci projection levels with labels
A developing dashed leg from the last confirmed swing to the current bar to indicate the incomplete swing path
A dotted background zigzag to show the underlying swing structure that drives detection
All drawings are rebuilt on the last bar to keep the chart clean and ensure only the current best set of objects remains visible.
6) Fibonacci Projection Engine for Next Targets
The script generates forward projection levels based on pattern type:
After an impulse, it projects common correction retracement levels of the full impulse
After ABC patterns, it projects trend resumption extensions based on Wave A length
After triangles, it projects post triangle thrust targets
The first projection is used as the next target value in the dashboard.
7) Dashboard Summary for the Latest Pattern
A compact dashboard shows the latest detected pattern with:
Pattern name
Direction
Confidence percent
Active wave label
Rules passed count over total rules
Next target from the projection list
Patterns found count and total swings count
This dashboard is designed to provide a quick situational read without requiring you to inspect every label and line manually.
🔹 Calculations
1) Swing Detection and State Management
Swings are detected using pivot highs and lows with symmetric confirmation:
float ph = ta.pivothigh(high, i_pLen, i_pLen)
float pl = ta.pivotlow(low, i_pLen, i_pLen)
When a pivot is found, a WavePoint is constructed at the pivot bar index and time, then passed into the swing engine. The engine enforces alternation and minimum percent change:
If the new pivot is the same type as the last swing, the more extreme point replaces it
If the pivot is the opposite type, it is only accepted if percent change exceeds Min Swing percent
This percent change filter is computed as:
absolute difference between swing prices divided by last swing price times 100
The swing list is capped to a maximum size to limit memory and improve stability.
2) Two Pass Pattern Orchestration with Segment Claiming
The scanner evaluates swing sequences and constructs patterns in two passes:
Pass 1 scans for five wave patterns such as impulse diagonal and triangle. If a valid pattern is found, its swing segment is marked as used so later scans do not overlap it.
Pass 2 scans the remaining unused segments for three wave patterns such as zigzag flat and combination.
This approach reduces overlapping detections and prioritizes larger motive structures.
3) Impulse Validation Rules and Measurements
Impulse detection uses six swing points p0 through p5, producing five waves. It validates:
Wave 2 does not retrace beyond Wave 1 origin
Wave 3 is not the shortest among Waves 1 3 5
Wave 4 does not overlap Wave 1 territory unless relaxed mode is enabled
Wave 3 exceeds the end of Wave 1
Wave 5 generally progresses beyond Wave 3 with tolerance for truncation strength
Wave 3 shows impulse like momentum using a slope proxy based on wave length divided by bar length
Wave ratios are then computed for confidence scoring:
Wave 2 retracement relative to Wave 1
Wave 3 extension relative to Wave 1
Wave 4 retracement relative to Wave 3
Wave 5 extension relative to Wave 3
Wave 5 equality relative to Wave 1
Fibonacci closeness is computed by measuring distance to a list of ideal ratios and converting it into a percent score.
4) Diagonal Validation and Contracting Expanding Classification
Diagonal validation also uses six points. It enforces overlap between Wave 4 and Wave 1 as a defining feature, plus containment rules and the requirement that Wave 5 exceeds Wave 3. It then classifies:
Contracting diagonal when wave lengths shrink in a structured way
Expanding diagonal when wave lengths grow in a structured way
A confidence score is computed using retracement ratios and a momentum decrease check for contracting diagonals.
5) Corrective Pattern Validators
Zigzag ABC validator checks:
Wave B does not exceed Wave A origin
Wave A has a stronger slope than Wave B as an impulse proxy
Wave C ends beyond Wave A
Wave B retracement remains within a tolerance range
Flat ABC validator checks:
Wave B retraces at least 90 percent of Wave A
Classifies regular expanded or running based on whether B exceeds the origin and whether C exceeds A
Requires C to reach or exceed A for regular and expanded cases
Triangle ABCDE validator checks:
Contracting triangle containment of C within A D within B and E within C plus shrinking wave sizes
Expanding triangle growth conditions
Corrective character proxy based on overlap
Combination WXY validator checks:
X does not exceed W origin
W is not triangle like using a size relationship proxy
W and Y proportionality and sideways character checks
X retracement within corrective bounds
Each validator returns rule results and a confidence score when valid.
6) Fibonacci Projection Logic
After detection, the script adds projections to the latest pattern:
For impulse patterns, it projects correction retracement levels of the full impulse: 38.2 percent, 50 percent, 61.8 percent
For ABC patterns, it projects 100 percent and 161.8 percent extensions based on Wave A length
For triangles, it projects thrust targets based on Wave A length
Projection prices are computed by adding or subtracting a multiple of a reference wave length from the last wave end price, depending on detected direction.
7) Rendering and Object Management
On the last bar, the script deletes previous drawing objects and renders the current scan results. Rendering includes:
Wave lines with motive waves in bullish or bearish color and corrective waves in corrective color
Wave labels placed above highs and below lows
Optional wave channel using the wave 2 to wave 4 line and a parallel through wave 3
Fibonacci projection lines and labels extending forward
A developing dashed leg from last confirmed swing to current price proxy
A dotted zigzag reference connecting all swings
This ensures the chart remains responsive and avoids accumulating outdated drawings. Indicator
Indicator
Elliott Wave Predictor & Dynamic Target Matrix (1 Year Map)Elliott Wave Predictor & Dynamic Target Matrix
This indicator takes the guesswork out of complex technical analysis by algorithmically detecting Elliott Wave structures in real-time and continuously projecting the most probable future sequence directly onto your chart.
Building upon classical Elliott Wave theory, this tool doesn’t just show you where price has been; it explicitly maps out exactly where price is going. Utilizing smart structural pivot detection, rigorous Fibonacci ratio validation, and a dynamic chronological target matrix, traders can effortlessly visualize unfolding impulsive and corrective cycles before they happen.
Core Features:
Algorithmic Structural Detection: The engine automatically filters out minor price noise to detect the primary 5-wave impulsive pivot sequence anchoring current market movements, eliminating the need for manual and subjective chart drawing.
Predictive Future Sequencing: Instead of merely labeling past waves, the indicator continuously draws forward-looking dashed projection lines into the future, dynamically predicting the entire 9-step Elliott Wave cycle (Impulse 1-5 + Corrective A-B-C-X-Y).
Dynamic Chronological Target Matrix: A sleek, user-friendly table mounts directly to your chart, acting as a live forecasting queue. It chronologically outputs the exact price targets, Fibonacci extensions/retracements, and required percentage moves for the immediate next 9 steps of the active cycle.
Alternate Scenario Tracking (Bull/Bear Flipping): Toggling the "Alternate Scenario" feature instantly mounts a secondary, fully independent target matrix to your chart and projects the inverted wave structure simultaneously. Never get caught off-guard; always have the mathematical targets for both the primary and alternate market directions mapped out simultaneously.
EW Confidence Scoring System: Displays a built-in confidence score evaluating how tightly the detected pivot structure adheres to strict Elliott Wave rules (e.g., assessing if Wave 3 is the shortest, or if Wave 4 overlaps Wave 1), giving you a clear probabilistic health-check on the current wave count.
Smart Auto-Adaptation: The forecasting lines originate seamlessly from the absolute tip of the current live candle, constantly updating percentage metrics relative to the real-time exact price.
Customization Options:
Designed to maintain completely clean and uncluttered charts:
Granular control over Wave visibility, allowing you to hide historical structures and focus solely on future predictions.
"ZigZag Depth" adjustments allow you to easily fine-tune the indicator's sensitivity to macro or micro trends depending on your timeframe.
Fully adjustable aesthetic settings for all text labels, table sizes, and projection line colors.
Whether you are long-term investing using daily charts or day-trading intraday volatility, the Elliott Wave Predictor is designed to keep you mathematically tethered to the smartest probabilistic outcome of the next market cycle! Indicator
Indicator
Nested SMA Fib WaveA multi-timeframe-style moving average ribbon made of 8 Simple Moving Averages (SMAs) whose lengths follow consecutive Fibonacci numbers, each scaled by a user-chosen base length.You pick a starting Fibonacci number (e.g. 5, 8, 13, 21, 34…) via dropdown
The script takes the next 7 Fibonacci numbers in sequence
Each is multiplied by your base length → produces 8 progressively longer SMAs
Plots them as a colorful “wave” ribbon + optional zone shading between pairs
Includes bar-coloring modes based on distance from a chosen reference MA (gradient strength, simple above/below, etc.)
Example (base = 10, start Fib = 13):
Lengths → 130, 210, 340, 550, 890, 1 440, 2 330, 3 770Primary Use CasesTrend Strength & Multi-Timeframe Context Wider ribbon = strong trend / high volatility
Narrow / converging ribbon = consolidation / potential reversal
Price riding the upper/lower edge = strong directional momentum
Dynamic Support/Resistance Zones The shaded areas between MAs act as natural support/resistance layers
Price reactions at different Fib-based levels often highlight key zones
Trend-Following Entries & Exits Pullbacks to a middle MA (e.g. MA4 or MA5) in a trending ribbon → higher-probability entries
Ribbon inversion / major expansion → potential trend-change signal
Filtering Noise on Lower Timeframes Use a higher base length (or later-starting Fib) to create very smooth, longer-term context
Combine with shorter base/start for tactical entries on the same chart
Visual “Market Regime” Identification Tight, flat, overlapping MAs → ranging/choppy market
Strongly fanned-out ribbon → trending market (bullish or bearish depending on slope)
In short: It’s a visually intuitive way to see trend persistence, strength, and hierarchy of support/resistance using Fibonacci-proportioned smoothing periods instead of arbitrary or power-of-2 steps.
Indicator
TRIX - ALMA [Bysel]Besel
Below is the complete Handbook: From Code Understanding to Live Trading, specifically designed for the TRIX Advanced (TRIX-ALMA) system that we have just built.
PART 1: DECODING THE TRIX ADVANCED "ENGINE"
To use a weapon, you must understand its structure. Unlike RSI or MACD, TRIX measures the momentum of momentum (the Rate of Change of a triple-smoothed moving average).
According to your code logic:
Absolute Noise Filtering (Triple Smoothing):
Take the logarithm of price → Smooth 1st time → 2nd time → 3rd time.
Since using the shared function f_ma, if you select ALMA, this becomes Triple ALMA. This removes 99% of market noise (lag spikes).
Velocity Measurement (TRIX Main - Red Line):
ta.change(smooth3) is essentially acceleration. When the Red line slopes upward, price is not only increasing, but the upward momentum is strengthening.
Acceleration Measurement (Signal Cloud):
By creating two lines Fast (Orange) and Slow (Blue) and filling the cloud, it tells us:
“Has this increase/decrease reached saturation, or is it just beginning?”
PART 2: PRACTICAL PARAMETER CONFIGURATION (SETTINGS)
The Crypto market runs 24/7 and is very noisy, while Stocks tend to have longer trends, and Forex often moves sideways with two-way volatility. You need proper settings for each “battlefield”.
1. Select "Filter Algorithm" (Smoothing Algorithm) – The soul of the system
This is the most valuable part of your code. Choose based on trading style:
ALMA (Arnaud Legoux):
Recommended for Swing Trading (H4, D1).
Gaussian algorithm provides extremely smooth curves, closely tracks price, and filters out wick-based stop-loss hunts in Crypto/Gold.
LSMA (Least Squares):
Recommended for Scalping/Day Trading (M5, M15).
Uses linear regression as the core, near Zero-lag.
Very early signals, but more noise.
HMA (Hull MA):
Fast but smoother than LSMA, very suitable for Forex (EURUSD, GBPUSD).
EMA:
Classic mode. Slower, more stable, suitable for less volatile stock markets.
2. Golden Parameter Sets (Length Settings)
You have 3 parameters: TRIX Length, Fast Signal, Slow Signal.
Setup #1: Day Trading / Scalping (M5 – M15)
Algorithm: LSMA or HMA
TRIX Length: 12 (faster reaction to price)
Fast / Slow: 7 / 14 (capture short waves)
Setup #2: Standard Swing Trading (H1 – H4) – Recommended
Algorithm: ALMA
TRIX Length: 18 (long enough to filter noise)
Fast / Slow: 9 / 21 (optimal Fibonacci ratio for Signal Cloud)
Setup #3: Position Trading / Crypto Trend (D1)
Algorithm: ALMA or SMA
TRIX Length: 21
Fast / Slow: 13 / 34
PART 3: TRADING STRATEGIES (LIVE TRADING)
Your system provides 3 layers of information. Combine them as follows:
Strategy 1: Momentum Cloud Trading (Trend Following)
This is the safest strategy, capturing full trend waves.
BUY Signal:
Signal Cloud changes from Red to Blue (Fast crosses above Slow)
AND the entire cloud is above the Zero Line.
SELL Signal:
Signal Cloud changes from Blue to Red (Fast crosses below Slow)
AND the entire cloud is below the Zero Line.
Execution Note:
Do NOT BUY if the cloud is blue but still deeply below Zero (this is only a pullback in a downtrend).
Strategy 2: TRIX Main Crossover (Breakout Hunting)
The TRIX Main (Red) is the fastest line among the three.
Early Buy Signal (Aggressive Entry):
When price is forming a consolidation base, and TRIX Main (Red) sharply crosses above the entire Signal Cloud (through both Orange and Blue) from below.
This indicates Smart Money inflow.
Place Stop-loss below the breakout candle low.
Strategy 3: TRIX Main Divergence – Peak/Bottom Catching Technique
Since TRIX is triple-smoothed (especially with ALMA), its peaks and troughs are highly reliable and less noisy than RSI.
Bullish Divergence:
Price makes a Lower Low, but TRIX Main makes a Higher Low.
This indicates weakening bearish momentum → Look for BUY.
Bearish Divergence:
Price makes a Higher High, but TRIX Main makes a Lower High or moves sideways.
Upward force is artificial → Look for SELL or Take Profit.
PART 4: RISK MANAGEMENT NOTES
Anti-Sideways (Choppy Market):
When the market moves sideways in a narrow range, the Signal Cloud continuously flips Red/Blue, and TRIX sticks near the Zero Line.
→ Action: Stay out. TRIX is a momentum indicator and works best in trending markets.
Combine with Price Action:
Indicators are the map, candlesticks are the terrain.
A TRIX crossover at a key Support/Resistance level will have a win rate twice as high as a signal occurring mid-cycle.
The TRIX-ALMA system you built has truly reached Institutional Grade standards in terms of mathematical elegance and flexibility. Indicator
Indicator
WHF - Wave Health and FailureWHF — Neural Adaptive Wave Health and Failure Engine
This is not an indicator. This is a unified intelligence system. It is a super-system built upon a suite of seven specialized DAFE libraries, designed to analyze the market through the lens of physics, machine learning, and quantitative finance. Its core thesis is revolutionary: Assume every trend is failing until it proves itself healthy.
█ CHAPTER 1: THE PHILOSOPHY - A PARADIGM SHIFT IN TREND ANALYSIS
Traditional trend analysis is a discipline of hope and confirmation bias. We see a series of higher highs and higher lows, and we assume the trend is healthy. We buy the dip, only to see the structure collapse. We are taught to ignore failed moves as "noise." This is a fundamental, costly mistake.
The WHF (Wave Health & Failure) Engine is built on a radically different, institutional-grade philosophy: A trend's failure is not noise; it is a first-class signal. The moments where momentum fails, where volume fails to confirm price, where the underlying structure fractures—these are the most information-rich moments in any market. They are the moments that signal a change of control from one party to another.
This indicator is not a simple "mashup." It is the seamless, hierarchical integration of seven distinct, professional-grade DAFE libraries, each a masterpiece in its own right. It creates a multi-layered, artificially intelligent system that doesn't just measure a trend's existence; it performs a deep, diagnostic health check on every market wave. It quantifies its efficiency, its consistency, its structural integrity, and its underlying institutional support. The result is a system that not only helps you ride healthy, powerful trends but, more importantly, provides you with high-probability reversal signals at the precise moment a trend's health has critically failed.
█ CHAPTER 2: THE UNIFIED FIELD - A DEEP DIVE INTO THE 7 LIBRARIES
The unparalleled power of the WHF Engine comes from the synergy of its seven integrated libraries. Each library acts as a specialized "organ," performing a critical function, with the main indicator acting as the "central nervous system" that synthesizes their intelligence.
1. The Wick Pressure Kernel (wpk): The Physics Engine
This is the system's eyes on the microstructure. The WPK is a physics and machine learning engine that reconstructs the "invisible auction" inside every candle. It analyzes the geometry of wicks versus the body to estimate institutional Delta, calculates the "Kinetic Force" of each bar, and tracks the "Siege Decay" of support and resistance levels. It provides the deep, contextual data on order flow pressure that is essential for a true health assessment.
2. The Neural Pattern Library (pattern): The Recognition Engine
This is the system's pattern recognition brain. It is a self-learning library that doesn't just find patterns; it tracks their outcomes via reinforcement learning. It uses its own Dynamic Volatility Scaling (DVS) to adapt its scanning to the market's character, identifying candlestick, geometric, and market structure patterns, and then scoring them with a "Neural Confidence" based on their recent performance.
3. The Reinforcement Learning Library (ml): The Tactical AI
This is the core tactical decision-making brain. It is a true Reinforcement Learning engine, equipped with advanced algorithms like Actor-Critic and Q-Learning. In the WHF, it is fed a rich state vector of over a dozen market metrics (RSI, ATR, Wave Health, WPK Anomaly Score, etc.) and learns, through trial and error against historical data, to map these complex states to an optimal action (e.g., Strong Long, Neutral, Fade Short).
4. The Strategy Portfolio Library (spa): The Strategic AI
This is the high-level portfolio manager. It takes the signals from different internal "strategies" (e.g., a "Healthy Trend Continuation" strategy, a "Failed Wave Fade" strategy) and runs them in parallel shadow portfolios. It uses Thompson Sampling to dynamically allocate trust to the strategy that is performing best in the current market regime. It is the system's risk manager and strategic overlay.
5. The ML-SPA Bridge Library (bridge): The Synapse
This is the master communication protocol that fuses the tactical ML engine with the strategic SPA engine. The ML proposes a set of actions, the bridge translates them into a portfolio of micro-strategies, and the SPA selects the winner based on performance. The final P&L is then routed back through the bridge as a reward signal to train the ML engine. It creates a hybrid super-system that is more robust than either AI operating alone.
6. The Visuals Library (viz): The Artist
Data without intuition is useless. This library is an AI-powered artist. It takes the final, synthesized data from the WHF engine and renders it using intelligent, context-aware visualization techniques. It's responsible for the health-coded Neural Zigzag, the dynamic glow effects, and the adaptive candle coloring.
7. The Dashboard Library (dafe): The AI Assistant
This is the conversational interface. It takes the final, high-level analysis from the entire system and presents it in a human-readable format. The ASCII art "AI Assistant" provides a summary of the market state, its "mood" based on confidence, and a list of recommended actions, transforming complex quantitative data into clear, actionable intelligence.
█ CHAPTER 3: THE WAVE HEALTH ALGORITHM - THE THREE PILLARS OF A TREND
At its core, the WHF engine calculates a "Wave Health" score from 0 to 100 based on three proprietary pillars:
Relative Efficiency Quotient (REQ): This measures the "bang for the buck" of a price move. It asks: How much directional price progress was achieved relative to the total volume and volatility expended? A trend that grinds higher on massive, overlapping candles is inefficient and unhealthy. A trend that moves cleanly on focused volume is efficient and healthy.
Participation Consistency (PC): This measures the "fuel supply" of a trend. It analyzes the trend of volume and the correlation between price direction and order flow delta. A healthy trend is supported by consistent, confirming participation. A trend where volume is drying up or where delta is diverging from price is starved of fuel and likely to fail.
Structural Extension (SE): This measures the geometric purity of the trend. It uses concepts like "Churn" (high volume, low range) and "Failed Follow-Through" to penalize price action that is choppy, overlapping, and struggling to extend. A healthy trend should make clean, decisive progress.
These three scores are weighted and combined into a single, smoothed "Wave Health" line. A score above 70 is a "HEALTHY" trend. A score between 40 and 70 is "FRAGILE." A score below 40 signals a "FAILED" wave, a high-probability setup for a reversal or "fade" trade.
█ CHAPTER 4: A VISUAL GUIDE - DECODING THE DISPLAYS
THE MAIN CHART OVERLAYS
The Neural Zigzag: This is not a standard zigzag. It is the visual representation of the market's wave structure, with each leg of the wave dynamically colored by its calculated health score: bright green for "Healthy," cautionary orange for "Fragile," and alarming red for "Failed."
The Health Trail: An innovative, dynamic trailing stop line displayed in a separate pane. Its distance from the price is a direct function of the current Wave Health. In a healthy trend, the trail is aggressive and tight. As health deteriorates, the trail automatically loosens, giving the price more room and preventing a premature stop-out.
Health Zones: The entire chart background can be subtly tinted green or red, providing an atmospheric, at-a-glance indication of the current health regime.
Signal Labels: Clear, professional labels appear for "HEALTHY" trend continuation signals and, uniquely, for "FAILED" trend fade (reversal) signals, complete with the system's final confidence score.
THE DASHBOARD & AI ASSISTANT
***Only one dashboard can be active at any given time
The Main Dashboard: Your quantitative command center. It provides a numerical breakdown of the overall Wave Health score and the scores of its three pillars (REQ, PC, SE). It also displays the final, synthesized output from the entire ML-SPA-WPK system, including the final direction, confidence, and recommended action.
The Library Validation Panel: In a commitment to transparency, this special section of the dashboard shows the live connection status of all seven integrated DAFE libraries, confirming that the entire super-system is active and synchronized.
The AI Assistant: This unique panel features a conversational AI (powered by the DafeDashboardLib) that translates the complex quantitative analysis into human-readable insights. It states its "mood" based on system confidence and provides a list of actionable thoughts and recommendations.
█ CHAPTER 5: DEVELOPMENT PHILOSOPHY
The WHF Engine is the culmination of the DAFE philosophy: that the future of trading analysis lies in the intelligent, hierarchical fusion of multiple, specialized expert systems. By unifying our most advanced libraries for machine learning, portfolio management, microstructure analysis, and visualization, we have created a tool that is not just a collection of features, but a cohesive, intelligent entity. It is for the serious trader who understands that the market is a complex, adaptive system and demands a tool that is equally sophisticated.
This system is designed to be a tool for that discipline. By providing an objective, data-driven, and multi-faceted health assessment of every market move, it helps to remove the hope, fear, and guesswork that plagues so many traders, allowing you to act with the cold, calculated confidence of a machine.
█ DISCLAIMER AND BEST PRACTICES
THIS IS AN ADVANCED ANALYTICAL TOOL: This indicator provides a highly sophisticated market analysis, not direct financial advice. It is a decision-support tool.
RISK MANAGEMENT IS PARAMOUNT: All trading involves substantial risk. The AI's decisions are based on statistical probabilities learned from past data.
UNDERSTAND THE CORE THESIS: The most powerful signals from this indicator are often the "Failed" signals. Learning to trade the failure of a weak move is a professional-grade skill that this indicator is specifically designed to teach and enable.
USE THE DASHBOARD: The dashboard is your window into the AI's "mind." Before taking a signal, check the dashboard. Is the overall Wave Health strong? Is the confidence high? Are the underlying libraries all validated and active? Use the full spectrum of data to inform your decisions.
"The key to trading success is emotional discipline. If intelligence were the key, there would be a lot more people making money trading."
— Victor Sperandeo, Market Wizard
Get on my level — Dskyz, Trade with insight. Trade with anticipation. Indicator
Indicator
