Liquidity Sweep & Reversal — Body Anchored + Risk (v6)Overview
The Liquidity Sweep & Reversal — Locked to Price (v6) indicator identifies liquidity sweeps around major swing highs and lows, confirming reversals when price closes back inside the swept level.
All signals are locked to price (bottom of green candle for BUY, top of red candle for SELL), so they remain perfectly aligned when zooming or scaling.
This indicator is ideal for swing traders and scalpers who trade reversals, liquidity events, and reclaim structures.
How It Works
Detects confirmed swing highs and lows using a pivot-based structure.
Waits for a liquidity sweep — when price wicks beyond a recent swing.
Confirms a reclaim when price closes back inside the previous swing level.
Triggers a BUY or SELL signal anchored to the candle body.
Automatically calculates stop loss and risk using ATR and your inputs.
Input Settings
Swing Detection
Swing Detection Strength: How many bars confirm a swing pivot. Higher = stronger swings.
Bars to Confirm Reclaim: Number of bars after a sweep for price to close back within the swing zone.
Swing Proximity %: How close price must come to a swing to count as a liquidity sweep.
Trend Filter (optional)
Use EMA Trend Filter: When enabled, only BUY in uptrend and SELL in downtrend.
Fast EMA Length / Slow EMA Length: Define EMAs used to detect trend direction.
Risk & Stop Management
ATR Length: Period for ATR calculation (volatility measurement).
Base ATR Stop Buffer (x ATR): Distance of stop loss from entry based on ATR multiplier.
Position Size (quote units): Your total position size in quote currency (e.g., USDT).
Risk % of (Position / 20): Defines how much of your position to risk per trade.
Example: (Position / 20) × Risk % = per-trade risk.
Chart Elements
BUY Arrow (green): Appears after a liquidity sweep and reclaim near a swing low.
SELL Arrow (red): Appears after a sweep and reclaim near a swing high.
Labels: Display entry price, stop loss (SL), and calculated risk dollar value.
EMAs: Optional fast/slow moving averages for directional bias.
Dynamic Stops: Adjust automatically using ATR × risk settings.
Trading Tips
Use BUY signals near liquidity sweeps under swing lows.
Use SELL signals near liquidity sweeps above swing highs.
Adjust swing length for different timeframes:
Lower values for scalping (3–5)
Higher values for swing trading (7–10)
Respect stop loss levels and use risk control settings for consistent sizing.
Combine with volume, OBV, or structure for confirmation.
Alerts
BUY — Locked to Price: "BUY: swing low reclaimed with dynamic stop."
SELL — Locked to Price: "SELL: swing high reclaimed with dynamic stop."
Best Use Cases
Liquidity-based reversals
Swing entry confirmation
Stop hunt reclaims
Structure-based entries
Author
Created by @roccodallas
For traders who value clean structure, risk control, and chart precision.
Indicators and strategies
Quantum Rotational Field MappingQuantum Rotational Field Mapping (QRFM):
Phase Coherence Detection Through Complex-Plane Oscillator Analysis
Quantum Rotational Field Mapping applies complex-plane mathematics and phase-space analysis to oscillator ensembles, identifying high-probability trend ignition points by measuring when multiple independent oscillators achieve phase coherence. Unlike traditional multi-oscillator approaches that simply stack indicators or use boolean AND/OR logic, this system converts each oscillator into a rotating phasor (vector) in the complex plane and calculates the Coherence Index (CI) —a mathematical measure of how tightly aligned the ensemble has become—then generates signals only when alignment, phase direction, and pairwise entanglement all converge.
The indicator combines three mathematical frameworks: phasor representation using analytic signal theory to extract phase and amplitude from each oscillator, coherence measurement using vector summation in the complex plane to quantify group alignment, and entanglement analysis that calculates pairwise phase agreement across all oscillator combinations. This creates a multi-dimensional confirmation system that distinguishes between random oscillator noise and genuine regime transitions.
What Makes This Original
Complex-Plane Phasor Framework
This indicator implements classical signal processing mathematics adapted for market oscillators. Each oscillator—whether RSI, MACD, Stochastic, CCI, Williams %R, MFI, ROC, or TSI—is first normalized to a common scale, then converted into a complex-plane representation using an in-phase (I) and quadrature (Q) component. The in-phase component is the oscillator value itself, while the quadrature component is calculated as the first difference (derivative proxy), creating a velocity-aware representation.
From these components, the system extracts:
Phase (φ) : Calculated as φ = atan2(Q, I), representing the oscillator's position in its cycle (mapped to -180° to +180°)
Amplitude (A) : Calculated as A = √(I² + Q²), representing the oscillator's strength or conviction
This mathematical approach is fundamentally different from simply reading oscillator values. A phasor captures both where an oscillator is in its cycle (phase angle) and how strongly it's expressing that position (amplitude). Two oscillators can have the same value but be in opposite phases of their cycles—traditional analysis would see them as identical, while QRFM sees them as 180° out of phase (contradictory).
Coherence Index Calculation
The core innovation is the Coherence Index (CI) , borrowed from physics and signal processing. When you have N oscillators, each with phase φₙ, you can represent each as a unit vector in the complex plane: e^(iφₙ) = cos(φₙ) + i·sin(φₙ).
The CI measures what happens when you sum all these vectors:
Resultant Vector : R = Σ e^(iφₙ) = Σ cos(φₙ) + i·Σ sin(φₙ)
Coherence Index : CI = |R| / N
Where |R| is the magnitude of the resultant vector and N is the number of active oscillators.
The CI ranges from 0 to 1:
CI = 1.0 : Perfect coherence—all oscillators have identical phase angles, vectors point in the same direction, creating maximum constructive interference
CI = 0.0 : Complete decoherence—oscillators are randomly distributed around the circle, vectors cancel out through destructive interference
0 < CI < 1 : Partial alignment—some clustering with some scatter
This is not a simple average or correlation. The CI captures phase synchronization across the entire ensemble simultaneously. When oscillators phase-lock (align their cycles), the CI spikes regardless of their individual values. This makes it sensitive to regime transitions that traditional indicators miss.
Dominant Phase and Direction Detection
Beyond measuring alignment strength, the system calculates the dominant phase of the ensemble—the direction the resultant vector points:
Dominant Phase : φ_dom = atan2(Σ sin(φₙ), Σ cos(φₙ))
This gives the "average direction" of all oscillator phases, mapped to -180° to +180°:
+90° to -90° (right half-plane): Bullish phase dominance
+90° to +180° or -90° to -180° (left half-plane): Bearish phase dominance
The combination of CI magnitude (coherence strength) and dominant phase angle (directional bias) creates a two-dimensional signal space. High CI alone is insufficient—you need high CI plus dominant phase pointing in a tradeable direction. This dual requirement is what separates QRFM from simple oscillator averaging.
Entanglement Matrix and Pairwise Coherence
While the CI measures global alignment, the entanglement matrix measures local pairwise relationships. For every pair of oscillators (i, j), the system calculates:
E(i,j) = |cos(φᵢ - φⱼ)|
This represents the phase agreement between oscillators i and j:
E = 1.0 : Oscillators are in-phase (0° or 360° apart)
E = 0.0 : Oscillators are in quadrature (90° apart, orthogonal)
E between 0 and 1 : Varying degrees of alignment
The system counts how many oscillator pairs exceed a user-defined entanglement threshold (e.g., 0.7). This entangled pairs count serves as a confirmation filter: signals require not just high global CI, but also a minimum number of strong pairwise agreements. This prevents false ignitions where CI is high but driven by only two oscillators while the rest remain scattered.
The entanglement matrix creates an N×N symmetric matrix that can be visualized as a web—when many cells are bright (high E values), the ensemble is highly interconnected. When cells are dark, oscillators are moving independently.
Phase-Lock Tolerance Mechanism
A complementary confirmation layer is the phase-lock detector . This calculates the maximum phase spread across all oscillators:
For all pairs (i,j), compute angular distance: Δφ = |φᵢ - φⱼ|, wrapping at 180°
Max Spread = maximum Δφ across all pairs
If max spread < user threshold (e.g., 35°), the ensemble is considered phase-locked —all oscillators are within a narrow angular band.
This differs from entanglement: entanglement measures pairwise cosine similarity (magnitude of alignment), while phase-lock measures maximum angular deviation (tightness of clustering). Both must be satisfied for the highest-conviction signals.
Multi-Layer Visual Architecture
QRFM includes six visual components that represent the same underlying mathematics from different perspectives:
Circular Orbit Plot : A polar coordinate grid showing each oscillator as a vector from origin to perimeter. Angle = phase, radius = amplitude. This is a real-time snapshot of the complex plane. When vectors converge (point in similar directions), coherence is high. When scattered randomly, coherence is low. Users can see phase alignment forming before CI numerically confirms it.
Phase-Time Heat Map : A 2D matrix with rows = oscillators and columns = time bins. Each cell is colored by the oscillator's phase at that time (using a gradient where color hue maps to angle). Horizontal color bands indicate sustained phase alignment over time. Vertical color bands show moments when all oscillators shared the same phase (ignition points). This provides historical pattern recognition.
Entanglement Web Matrix : An N×N grid showing E(i,j) for all pairs. Cells are colored by entanglement strength—bright yellow/gold for high E, dark gray for low E. This reveals which oscillators are driving coherence and which are lagging. For example, if RSI and MACD show high E but Stochastic shows low E with everything, Stochastic is the outlier.
Quantum Field Cloud : A background color overlay on the price chart. Color (green = bullish, red = bearish) is determined by dominant phase. Opacity is determined by CI—high CI creates dense, opaque cloud; low CI creates faint, nearly invisible cloud. This gives an atmospheric "feel" for regime strength without looking at numbers.
Phase Spiral : A smoothed plot of dominant phase over recent history, displayed as a curve that wraps around price. When the spiral is tight and rotating steadily, the ensemble is in coherent rotation (trending). When the spiral is loose or erratic, coherence is breaking down.
Dashboard : A table showing real-time metrics: CI (as percentage), dominant phase (in degrees with directional arrow), field strength (CI × average amplitude), entangled pairs count, phase-lock status (locked/unlocked), quantum state classification ("Ignition", "Coherent", "Collapse", "Chaos"), and collapse risk (recent CI change normalized to 0-100%).
Each component is independently toggleable, allowing users to customize their workspace. The orbit plot is the most essential—it provides intuitive, visual feedback on phase alignment that no numerical dashboard can match.
Core Components and How They Work Together
1. Oscillator Normalization Engine
The foundation is creating a common measurement scale. QRFM supports eight oscillators:
RSI : Normalized from to using overbought/oversold levels (70, 30) as anchors
MACD Histogram : Normalized by dividing by rolling standard deviation, then clamped to
Stochastic %K : Normalized from using (80, 20) anchors
CCI : Divided by 200 (typical extreme level), clamped to
Williams %R : Normalized from using (-20, -80) anchors
MFI : Normalized from using (80, 20) anchors
ROC : Divided by 10, clamped to
TSI : Divided by 50, clamped to
Each oscillator can be individually enabled/disabled. Only active oscillators contribute to phase calculations. The normalization removes scale differences—a reading of +0.8 means "strongly bullish" regardless of whether it came from RSI or TSI.
2. Analytic Signal Construction
For each active oscillator at each bar, the system constructs the analytic signal:
In-Phase (I) : The normalized oscillator value itself
Quadrature (Q) : The bar-to-bar change in the normalized value (first derivative approximation)
This creates a 2D representation: (I, Q). The phase is extracted as:
φ = atan2(Q, I) × (180 / π)
This maps the oscillator to a point on the unit circle. An oscillator at the same value but rising (positive Q) will have a different phase than one that is falling (negative Q). This velocity-awareness is critical—it distinguishes between "at resistance and stalling" versus "at resistance and breaking through."
The amplitude is extracted as:
A = √(I² + Q²)
This represents the distance from origin in the (I, Q) plane. High amplitude means the oscillator is far from neutral (strong conviction). Low amplitude means it's near zero (weak/transitional state).
3. Coherence Calculation Pipeline
For each bar (or every Nth bar if phase sample rate > 1 for performance):
Step 1 : Extract phase φₙ for each of the N active oscillators
Step 2 : Compute complex exponentials: Zₙ = e^(i·φₙ·π/180) = cos(φₙ·π/180) + i·sin(φₙ·π/180)
Step 3 : Sum the complex exponentials: R = Σ Zₙ = (Σ cos φₙ) + i·(Σ sin φₙ)
Step 4 : Calculate magnitude: |R| = √
Step 5 : Normalize by count: CI_raw = |R| / N
Step 6 : Smooth the CI: CI = SMA(CI_raw, smoothing_window)
The smoothing step (default 2 bars) removes single-bar noise spikes while preserving structural coherence changes. Users can adjust this to control reactivity versus stability.
The dominant phase is calculated as:
φ_dom = atan2(Σ sin φₙ, Σ cos φₙ) × (180 / π)
This is the angle of the resultant vector R in the complex plane.
4. Entanglement Matrix Construction
For all unique pairs of oscillators (i, j) where i < j:
Step 1 : Get phases φᵢ and φⱼ
Step 2 : Compute phase difference: Δφ = φᵢ - φⱼ (in radians)
Step 3 : Calculate entanglement: E(i,j) = |cos(Δφ)|
Step 4 : Store in symmetric matrix: matrix = matrix = E(i,j)
The matrix is then scanned: count how many E(i,j) values exceed the user-defined threshold (default 0.7). This count is the entangled pairs metric.
For visualization, the matrix is rendered as an N×N table where cell brightness maps to E(i,j) intensity.
5. Phase-Lock Detection
Step 1 : For all unique pairs (i, j), compute angular distance: Δφ = |φᵢ - φⱼ|
Step 2 : Wrap angles: if Δφ > 180°, set Δφ = 360° - Δφ
Step 3 : Find maximum: max_spread = max(Δφ) across all pairs
Step 4 : Compare to tolerance: phase_locked = (max_spread < tolerance)
If phase_locked is true, all oscillators are within the specified angular cone (e.g., 35°). This is a boolean confirmation filter.
6. Signal Generation Logic
Signals are generated through multi-layer confirmation:
Long Ignition Signal :
CI crosses above ignition threshold (e.g., 0.80)
AND dominant phase is in bullish range (-90° < φ_dom < +90°)
AND phase_locked = true
AND entangled_pairs >= minimum threshold (e.g., 4)
Short Ignition Signal :
CI crosses above ignition threshold
AND dominant phase is in bearish range (φ_dom < -90° OR φ_dom > +90°)
AND phase_locked = true
AND entangled_pairs >= minimum threshold
Collapse Signal :
CI at bar minus CI at current bar > collapse threshold (e.g., 0.55)
AND CI at bar was above 0.6 (must collapse from coherent state, not from already-low state)
These are strict conditions. A high CI alone does not generate a signal—dominant phase must align with direction, oscillators must be phase-locked, and sufficient pairwise entanglement must exist. This multi-factor gating dramatically reduces false signals compared to single-condition triggers.
Calculation Methodology
Phase 1: Oscillator Computation and Normalization
On each bar, the system calculates the raw values for all enabled oscillators using standard Pine Script functions:
RSI: ta.rsi(close, length)
MACD: ta.macd() returning histogram component
Stochastic: ta.stoch() smoothed with ta.sma()
CCI: ta.cci(close, length)
Williams %R: ta.wpr(length)
MFI: ta.mfi(hlc3, length)
ROC: ta.roc(close, length)
TSI: ta.tsi(close, short, long)
Each raw value is then passed through a normalization function:
normalize(value, overbought_level, oversold_level) = 2 × (value - oversold) / (overbought - oversold) - 1
This maps the oscillator's typical range to , where -1 represents extreme bearish, 0 represents neutral, and +1 represents extreme bullish.
For oscillators without fixed ranges (MACD, ROC, TSI), statistical normalization is used: divide by a rolling standard deviation or fixed divisor, then clamp to .
Phase 2: Phasor Extraction
For each normalized oscillator value val:
I = val (in-phase component)
Q = val - val (quadrature component, first difference)
Phase calculation:
phi_rad = atan2(Q, I)
phi_deg = phi_rad × (180 / π)
Amplitude calculation:
A = √(I² + Q²)
These values are stored in arrays: osc_phases and osc_amps for each oscillator n.
Phase 3: Complex Summation and Coherence
Initialize accumulators:
sum_cos = 0
sum_sin = 0
For each oscillator n = 0 to N-1:
phi_rad = osc_phases × (π / 180)
sum_cos += cos(phi_rad)
sum_sin += sin(phi_rad)
Resultant magnitude:
resultant_mag = √(sum_cos² + sum_sin²)
Coherence Index (raw):
CI_raw = resultant_mag / N
Smoothed CI:
CI = SMA(CI_raw, smoothing_window)
Dominant phase:
phi_dom_rad = atan2(sum_sin, sum_cos)
phi_dom_deg = phi_dom_rad × (180 / π)
Phase 4: Entanglement Matrix Population
For i = 0 to N-2:
For j = i+1 to N-1:
phi_i = osc_phases × (π / 180)
phi_j = osc_phases × (π / 180)
delta_phi = phi_i - phi_j
E = |cos(delta_phi)|
matrix_index_ij = i × N + j
matrix_index_ji = j × N + i
entangle_matrix = E
entangle_matrix = E
if E >= threshold:
entangled_pairs += 1
The matrix uses flat array storage with index mapping: index(row, col) = row × N + col.
Phase 5: Phase-Lock Check
max_spread = 0
For i = 0 to N-2:
For j = i+1 to N-1:
delta = |osc_phases - osc_phases |
if delta > 180:
delta = 360 - delta
max_spread = max(max_spread, delta)
phase_locked = (max_spread < tolerance)
Phase 6: Signal Evaluation
Ignition Long :
ignition_long = (CI crosses above threshold) AND
(phi_dom > -90 AND phi_dom < 90) AND
phase_locked AND
(entangled_pairs >= minimum)
Ignition Short :
ignition_short = (CI crosses above threshold) AND
(phi_dom < -90 OR phi_dom > 90) AND
phase_locked AND
(entangled_pairs >= minimum)
Collapse :
CI_prev = CI
collapse = (CI_prev - CI > collapse_threshold) AND (CI_prev > 0.6)
All signals are evaluated on bar close. The crossover and crossunder functions ensure signals fire only once when conditions transition from false to true.
Phase 7: Field Strength and Visualization Metrics
Average Amplitude :
avg_amp = (Σ osc_amps ) / N
Field Strength :
field_strength = CI × avg_amp
Collapse Risk (for dashboard):
collapse_risk = (CI - CI) / max(CI , 0.1)
collapse_risk_pct = clamp(collapse_risk × 100, 0, 100)
Quantum State Classification :
if (CI > threshold AND phase_locked):
state = "Ignition"
else if (CI > 0.6):
state = "Coherent"
else if (collapse):
state = "Collapse"
else:
state = "Chaos"
Phase 8: Visual Rendering
Orbit Plot : For each oscillator, convert polar (phase, amplitude) to Cartesian (x, y) for grid placement:
radius = amplitude × grid_center × 0.8
x = radius × cos(phase × π/180)
y = radius × sin(phase × π/180)
col = center + x (mapped to grid coordinates)
row = center - y
Heat Map : For each oscillator row and time column, retrieve historical phase value at lookback = (columns - col) × sample_rate, then map phase to color using a hue gradient.
Entanglement Web : Render matrix as table cell with background color opacity = E(i,j).
Field Cloud : Background color = (phi_dom > -90 AND phi_dom < 90) ? green : red, with opacity = mix(min_opacity, max_opacity, CI).
All visual components render only on the last bar (barstate.islast) to minimize computational overhead.
How to Use This Indicator
Step 1 : Apply QRFM to your chart. It works on all timeframes and asset classes, though 15-minute to 4-hour timeframes provide the best balance of responsiveness and noise reduction.
Step 2 : Enable the dashboard (default: top right) and the circular orbit plot (default: middle left). These are your primary visual feedback tools.
Step 3 : Optionally enable the heat map, entanglement web, and field cloud based on your preference. New users may find all visuals overwhelming; start with dashboard + orbit plot.
Step 4 : Observe for 50-100 bars to let the indicator establish baseline coherence patterns. Markets have different "normal" CI ranges—some instruments naturally run higher or lower coherence.
Understanding the Circular Orbit Plot
The orbit plot is a polar grid showing oscillator vectors in real-time:
Center point : Neutral (zero phase and amplitude)
Each vector : A line from center to a point on the grid
Vector angle : The oscillator's phase (0° = right/east, 90° = up/north, 180° = left/west, -90° = down/south)
Vector length : The oscillator's amplitude (short = weak signal, long = strong signal)
Vector label : First letter of oscillator name (R = RSI, M = MACD, etc.)
What to watch :
Convergence : When all vectors cluster in one quadrant or sector, CI is rising and coherence is forming. This is your pre-signal warning.
Scatter : When vectors point in random directions (360° spread), CI is low and the market is in a non-trending or transitional regime.
Rotation : When the cluster rotates smoothly around the circle, the ensemble is in coherent oscillation—typically seen during steady trends.
Sudden flips : When the cluster rapidly jumps from one side to the opposite (e.g., +90° to -90°), a phase reversal has occurred—often coinciding with trend reversals.
Example: If you see RSI, MACD, and Stochastic all pointing toward 45° (northeast) with long vectors, while CCI, TSI, and ROC point toward 40-50° as well, coherence is high and dominant phase is bullish. Expect an ignition signal if CI crosses threshold.
Reading Dashboard Metrics
The dashboard provides numerical confirmation of what the orbit plot shows visually:
CI : Displays as 0-100%. Above 70% = high coherence (strong regime), 40-70% = moderate, below 40% = low (poor conditions for trend entries).
Dom Phase : Angle in degrees with directional arrow. ⬆ = bullish bias, ⬇ = bearish bias, ⬌ = neutral.
Field Strength : CI weighted by amplitude. High values (> 0.6) indicate not just alignment but strong alignment.
Entangled Pairs : Count of oscillator pairs with E > threshold. Higher = more confirmation. If minimum is set to 4, you need at least 4 pairs entangled for signals.
Phase Lock : 🔒 YES (all oscillators within tolerance) or 🔓 NO (spread too wide).
State : Real-time classification:
🚀 IGNITION: CI just crossed threshold with phase-lock
⚡ COHERENT: CI is high and stable
💥 COLLAPSE: CI has dropped sharply
🌀 CHAOS: Low CI, scattered phases
Collapse Risk : 0-100% scale based on recent CI change. Above 50% warns of imminent breakdown.
Interpreting Signals
Long Ignition (Blue Triangle Below Price) :
Occurs when CI crosses above threshold (e.g., 0.80)
Dominant phase is in bullish range (-90° to +90°)
All oscillators are phase-locked (within tolerance)
Minimum entangled pairs requirement met
Interpretation : The oscillator ensemble has transitioned from disorder to coherent bullish alignment. This is a high-probability long entry point. The multi-layer confirmation (CI + phase direction + lock + entanglement) ensures this is not a single-oscillator whipsaw.
Short Ignition (Red Triangle Above Price) :
Same conditions as long, but dominant phase is in bearish range (< -90° or > +90°)
Interpretation : Coherent bearish alignment has formed. High-probability short entry.
Collapse (Circles Above and Below Price) :
CI has dropped by more than the collapse threshold (e.g., 0.55) over a 5-bar window
CI was previously above 0.6 (collapsing from coherent state)
Interpretation : Phase coherence has broken down. If you are in a position, this is an exit warning. If looking to enter, stand aside—regime is transitioning.
Phase-Time Heat Map Patterns
Enable the heat map and position it at bottom right. The rows represent individual oscillators, columns represent time bins (most recent on left).
Pattern: Horizontal Color Bands
If a row (e.g., RSI) shows consistent color across columns (say, green for several bins), that oscillator has maintained stable phase over time. If all rows show horizontal bands of similar color, the entire ensemble has been phase-locked for an extended period—this is a strong trending regime.
Pattern: Vertical Color Bands
If a column (single time bin) shows all cells with the same or very similar color, that moment in time had high coherence. These vertical bands often align with ignition signals or major price pivots.
Pattern: Rainbow Chaos
If cells are random colors (red, green, yellow mixed with no pattern), coherence is low. The ensemble is scattered. Avoid trading during these periods unless you have external confirmation.
Pattern: Color Transition
If you see a row transition from red to green (or vice versa) sharply, that oscillator has phase-flipped. If multiple rows do this simultaneously, a regime change is underway.
Entanglement Web Analysis
Enable the web matrix (default: opposite corner from heat map). It shows an N×N grid where N = number of active oscillators.
Bright Yellow/Gold Cells : High pairwise entanglement. For example, if the RSI-MACD cell is bright gold, those two oscillators are moving in phase. If the RSI-Stochastic cell is bright, they are entangled as well.
Dark Gray Cells : Low entanglement. Oscillators are decorrelated or in quadrature.
Diagonal : Always marked with "—" because an oscillator is always perfectly entangled with itself.
How to use :
Scan for clustering: If most cells are bright, coherence is high across the board. If only a few cells are bright, coherence is driven by a subset (e.g., RSI and MACD are aligned, but nothing else is—weak signal).
Identify laggards: If one row/column is entirely dark, that oscillator is the outlier. You may choose to disable it or monitor for when it joins the group (late confirmation).
Watch for web formation: During low-coherence periods, the matrix is mostly dark. As coherence builds, cells begin lighting up. A sudden "web" of connections forming visually precedes ignition signals.
Trading Workflow
Step 1: Monitor Coherence Level
Check the dashboard CI metric or observe the orbit plot. If CI is below 40% and vectors are scattered, conditions are poor for trend entries. Wait.
Step 2: Detect Coherence Building
When CI begins rising (say, from 30% to 50-60%) and you notice vectors on the orbit plot starting to cluster, coherence is forming. This is your alert phase—do not enter yet, but prepare.
Step 3: Confirm Phase Direction
Check the dominant phase angle and the orbit plot quadrant where clustering is occurring:
Clustering in right half (0° to ±90°): Bullish bias forming
Clustering in left half (±90° to 180°): Bearish bias forming
Verify the dashboard shows the corresponding directional arrow (⬆ or ⬇).
Step 4: Wait for Signal Confirmation
Do not enter based on rising CI alone. Wait for the full ignition signal:
CI crosses above threshold
Phase-lock indicator shows 🔒 YES
Entangled pairs count >= minimum
Directional triangle appears on chart
This ensures all layers have aligned.
Step 5: Execute Entry
Long : Blue triangle below price appears → enter long
Short : Red triangle above price appears → enter short
Step 6: Position Management
Initial Stop : Place stop loss based on your risk management rules (e.g., recent swing low/high, ATR-based buffer).
Monitoring :
Watch the field cloud density. If it remains opaque and colored in your direction, the regime is intact.
Check dashboard collapse risk. If it rises above 50%, prepare for exit.
Monitor the orbit plot. If vectors begin scattering or the cluster flips to the opposite side, coherence is breaking.
Exit Triggers :
Collapse signal fires (circles appear)
Dominant phase flips to opposite half-plane
CI drops below 40% (coherence lost)
Price hits your profit target or trailing stop
Step 7: Post-Exit Analysis
After exiting, observe whether a new ignition forms in the opposite direction (reversal) or if CI remains low (transition to range). Use this to decide whether to re-enter, reverse, or stand aside.
Best Practices
Use Price Structure as Context
QRFM identifies when coherence forms but does not specify where price will go. Combine ignition signals with support/resistance levels, trendlines, or chart patterns. For example:
Long ignition near a major support level after a pullback: high-probability bounce
Long ignition in the middle of a range with no structure: lower probability
Multi-Timeframe Confirmation
Open QRFM on two timeframes simultaneously:
Higher timeframe (e.g., 4-hour): Use CI level to determine regime bias. If 4H CI is above 60% and dominant phase is bullish, the market is in a bullish regime.
Lower timeframe (e.g., 15-minute): Execute entries on ignition signals that align with the higher timeframe bias.
This prevents counter-trend trades and increases win rate.
Distinguish Between Regime Types
High CI, stable dominant phase (State: Coherent) : Trending market. Ignitions are continuation signals; collapses are profit-taking or reversal warnings.
Low CI, erratic dominant phase (State: Chaos) : Ranging or choppy market. Avoid ignition signals or reduce position size. Wait for coherence to establish.
Moderate CI with frequent collapses : Whipsaw environment. Use wider stops or stand aside.
Adjust Parameters to Instrument and Timeframe
Crypto/Forex (high volatility) : Lower ignition threshold (0.65-0.75), lower CI smoothing (2-3), shorter oscillator lengths (7-10).
Stocks/Indices (moderate volatility) : Standard settings (threshold 0.75-0.85, smoothing 5-7, oscillator lengths 14).
Lower timeframes (5-15 min) : Reduce phase sample rate to 1-2 for responsiveness.
Higher timeframes (daily+) : Increase CI smoothing and oscillator lengths for noise reduction.
Use Entanglement Count as Conviction Filter
The minimum entangled pairs setting controls signal strictness:
Low (1-2) : More signals, lower quality (acceptable if you have other confirmation)
Medium (3-5) : Balanced (recommended for most traders)
High (6+) : Very strict, fewer signals, highest quality
Adjust based on your trade frequency preference and risk tolerance.
Monitor Oscillator Contribution
Use the entanglement web to see which oscillators are driving coherence. If certain oscillators are consistently dark (low E with all others), they may be adding noise. Consider disabling them. For example:
On low-volume instruments, MFI may be unreliable → disable MFI
On strongly trending instruments, mean-reversion oscillators (Stochastic, RSI) may lag → reduce weight or disable
Respect the Collapse Signal
Collapse events are early warnings. Price may continue in the original direction for several bars after collapse fires, but the underlying regime has weakened. Best practice:
If in profit: Take partial or full profit on collapse
If at breakeven/small loss: Exit immediately
If collapse occurs shortly after entry: Likely a false ignition; exit to avoid drawdown
Collapses do not guarantee immediate reversals—they signal uncertainty .
Combine with Volume Analysis
If your instrument has reliable volume:
Ignitions with expanding volume: Higher conviction
Ignitions with declining volume: Weaker, possibly false
Collapses with volume spikes: Strong reversal signal
Collapses with low volume: May just be consolidation
Volume is not built into QRFM (except via MFI), so add it as external confirmation.
Observe the Phase Spiral
The spiral provides a quick visual cue for rotation consistency:
Tight, smooth spiral : Ensemble is rotating coherently (trending)
Loose, erratic spiral : Phase is jumping around (ranging or transitional)
If the spiral tightens, coherence is building. If it loosens, coherence is dissolving.
Do Not Overtrade Low-Coherence Periods
When CI is persistently below 40% and the state is "Chaos," the market is not in a regime where phase analysis is predictive. During these times:
Reduce position size
Widen stops
Wait for coherence to return
QRFM's strength is regime detection. If there is no regime, the tool correctly signals "stand aside."
Use Alerts Strategically
Set alerts for:
Long Ignition
Short Ignition
Collapse
Phase Lock (optional)
Configure alerts to "Once per bar close" to avoid intrabar repainting and noise. When an alert fires, manually verify:
Orbit plot shows clustering
Dashboard confirms all conditions
Price structure supports the trade
Do not blindly trade alerts—use them as prompts for analysis.
Ideal Market Conditions
Best Performance
Instruments :
Liquid, actively traded markets (major forex pairs, large-cap stocks, major indices, top-tier crypto)
Instruments with clear cyclical oscillator behavior (avoid extremely illiquid or manipulated markets)
Timeframes :
15-minute to 4-hour: Optimal balance of noise reduction and responsiveness
1-hour to daily: Slower, higher-conviction signals; good for swing trading
5-minute: Acceptable for scalping if parameters are tightened and you accept more noise
Market Regimes :
Trending markets with periodic retracements (where oscillators cycle through phases predictably)
Breakout environments (coherence forms before/during breakout; collapse occurs at exhaustion)
Rotational markets with clear swings (oscillators phase-lock at turning points)
Volatility :
Moderate to high volatility (oscillators have room to move through their ranges)
Stable volatility regimes (sudden VIX spikes or flash crashes may create false collapses)
Challenging Conditions
Instruments :
Very low liquidity markets (erratic price action creates unstable oscillator phases)
Heavily news-driven instruments (fundamentals may override technical coherence)
Highly correlated instruments (oscillators may all reflect the same underlying factor, reducing independence)
Market Regimes :
Deep, prolonged consolidation (oscillators remain near neutral, CI is chronically low, few signals fire)
Extreme chop with no directional bias (oscillators whipsaw, coherence never establishes)
Gap-driven markets (large overnight gaps create phase discontinuities)
Timeframes :
Sub-5-minute charts: Noise dominates; oscillators flip rapidly; coherence is fleeting and unreliable
Weekly/monthly: Oscillators move extremely slowly; signals are rare; better suited for long-term positioning than active trading
Special Cases :
During major economic releases or earnings: Oscillators may lag price or become decorrelated as fundamentals overwhelm technicals. Reduce position size or stand aside.
In extremely low-volatility environments (e.g., holiday periods): Oscillators compress to neutral, CI may be artificially high due to lack of movement, but signals lack follow-through.
Adaptive Behavior
QRFM is designed to self-adapt to poor conditions:
When coherence is genuinely absent, CI remains low and signals do not fire
When only a subset of oscillators aligns, entangled pairs count stays below threshold and signals are filtered out
When phase-lock cannot be achieved (oscillators too scattered), the lock filter prevents signals
This means the indicator will naturally produce fewer (or zero) signals during unfavorable conditions, rather than generating false signals. This is a feature —it keeps you out of low-probability trades.
Parameter Optimization by Trading Style
Scalping (5-15 Minute Charts)
Goal : Maximum responsiveness, accept higher noise
Oscillator Lengths :
RSI: 7-10
MACD: 8/17/6
Stochastic: 8-10, smooth 2-3
CCI: 14-16
Others: 8-12
Coherence Settings :
CI Smoothing Window: 2-3 bars (fast reaction)
Phase Sample Rate: 1 (every bar)
Ignition Threshold: 0.65-0.75 (lower for more signals)
Collapse Threshold: 0.40-0.50 (earlier exit warnings)
Confirmation :
Phase Lock Tolerance: 40-50° (looser, easier to achieve)
Min Entangled Pairs: 2-3 (fewer oscillators required)
Visuals :
Orbit Plot + Dashboard only (reduce screen clutter for fast decisions)
Disable heavy visuals (heat map, web) for performance
Alerts :
Enable all ignition and collapse alerts
Set to "Once per bar close"
Day Trading (15-Minute to 1-Hour Charts)
Goal : Balance between responsiveness and reliability
Oscillator Lengths :
RSI: 14 (standard)
MACD: 12/26/9 (standard)
Stochastic: 14, smooth 3
CCI: 20
Others: 10-14
Coherence Settings :
CI Smoothing Window: 3-5 bars (balanced)
Phase Sample Rate: 2-3
Ignition Threshold: 0.75-0.85 (moderate selectivity)
Collapse Threshold: 0.50-0.55 (balanced exit timing)
Confirmation :
Phase Lock Tolerance: 30-40° (moderate tightness)
Min Entangled Pairs: 4-5 (reasonable confirmation)
Visuals :
Orbit Plot + Dashboard + Heat Map or Web (choose one)
Field Cloud for regime backdrop
Alerts :
Ignition and collapse alerts
Optional phase-lock alert for advance warning
Swing Trading (4-Hour to Daily Charts)
Goal : High-conviction signals, minimal noise, fewer trades
Oscillator Lengths :
RSI: 14-21
MACD: 12/26/9 or 19/39/9 (longer variant)
Stochastic: 14-21, smooth 3-5
CCI: 20-30
Others: 14-20
Coherence Settings :
CI Smoothing Window: 5-10 bars (very smooth)
Phase Sample Rate: 3-5
Ignition Threshold: 0.80-0.90 (high bar for entry)
Collapse Threshold: 0.55-0.65 (only significant breakdowns)
Confirmation :
Phase Lock Tolerance: 20-30° (tight clustering required)
Min Entangled Pairs: 5-7 (strong confirmation)
Visuals :
All modules enabled (you have time to analyze)
Heat Map for multi-bar pattern recognition
Web for deep confirmation analysis
Alerts :
Ignition and collapse
Review manually before entering (no rush)
Position/Long-Term Trading (Daily to Weekly Charts)
Goal : Rare, very high-conviction regime shifts
Oscillator Lengths :
RSI: 21-30
MACD: 19/39/9 or 26/52/12
Stochastic: 21, smooth 5
CCI: 30-50
Others: 20-30
Coherence Settings :
CI Smoothing Window: 10-14 bars
Phase Sample Rate: 5 (every 5th bar to reduce computation)
Ignition Threshold: 0.85-0.95 (only extreme alignment)
Collapse Threshold: 0.60-0.70 (major regime breaks only)
Confirmation :
Phase Lock Tolerance: 15-25° (very tight)
Min Entangled Pairs: 6+ (broad consensus required)
Visuals :
Dashboard + Orbit Plot for quick checks
Heat Map to study historical coherence patterns
Web to verify deep entanglement
Alerts :
Ignition only (collapses are less critical on long timeframes)
Manual review with fundamental analysis overlay
Performance Optimization (Low-End Systems)
If you experience lag or slow rendering:
Reduce Visual Load :
Orbit Grid Size: 8-10 (instead of 12+)
Heat Map Time Bins: 5-8 (instead of 10+)
Disable Web Matrix entirely if not needed
Disable Field Cloud and Phase Spiral
Reduce Calculation Frequency :
Phase Sample Rate: 5-10 (calculate every 5-10 bars)
Max History Depth: 100-200 (instead of 500+)
Disable Unused Oscillators :
If you only want RSI, MACD, and Stochastic, disable the other five. Fewer oscillators = smaller matrices, faster loops.
Simplify Dashboard :
Choose "Small" dashboard size
Reduce number of metrics displayed
These settings will not significantly degrade signal quality (signals are based on bar-close calculations, which remain accurate), but will improve chart responsiveness.
Important Disclaimers
This indicator is a technical analysis tool designed to identify periods of phase coherence across an ensemble of oscillators. It is not a standalone trading system and does not guarantee profitable trades. The Coherence Index, dominant phase, and entanglement metrics are mathematical calculations applied to historical price data—they measure past oscillator behavior and do not predict future price movements with certainty.
No Predictive Guarantee : High coherence indicates that oscillators are currently aligned, which historically has coincided with trending or directional price movement. However, past alignment does not guarantee future trends. Markets can remain coherent while prices consolidate, or lose coherence suddenly due to news, liquidity changes, or other factors not captured by oscillator mathematics.
Signal Confirmation is Probabilistic : The multi-layer confirmation system (CI threshold + dominant phase + phase-lock + entanglement) is designed to filter out low-probability setups. This increases the proportion of valid signals relative to false signals, but does not eliminate false signals entirely. Users should combine QRFM with additional analysis—support and resistance levels, volume confirmation, multi-timeframe alignment, and fundamental context—before executing trades.
Collapse Signals are Warnings, Not Reversals : A coherence collapse indicates that the oscillator ensemble has lost alignment. This often precedes trend exhaustion or reversals, but can also occur during healthy pullbacks or consolidations. Price may continue in the original direction after a collapse. Use collapses as risk management cues (tighten stops, take partial profits) rather than automatic reversal entries.
Market Regime Dependency : QRFM performs best in markets where oscillators exhibit cyclical, mean-reverting behavior and where trends are punctuated by retracements. In markets dominated by fundamental shocks, gap openings, or extreme low-liquidity conditions, oscillator coherence may be less reliable. During such periods, reduce position size or stand aside.
Risk Management is Essential : All trading involves risk of loss. Use appropriate stop losses, position sizing, and risk-per-trade limits. The indicator does not specify stop loss or take profit levels—these must be determined by the user based on their risk tolerance and account size. Never risk more than you can afford to lose.
Parameter Sensitivity : The indicator's behavior changes with input parameters. Aggressive settings (low thresholds, loose tolerances) produce more signals with lower average quality. Conservative settings (high thresholds, tight tolerances) produce fewer signals with higher average quality. Users should backtest and forward-test parameter sets on their specific instruments and timeframes before committing real capital.
No Repainting by Design : All signal conditions are evaluated on bar close using bar-close values. However, the visual components (orbit plot, heat map, dashboard) update in real-time during bar formation for monitoring purposes. For trade execution, rely on the confirmed signals (triangles and circles) that appear only after the bar closes.
Computational Load : QRFM performs extensive calculations, including nested loops for entanglement matrices and real-time table rendering. On lower-powered devices or when running multiple indicators simultaneously, users may experience lag. Use the performance optimization settings (reduce visual complexity, increase phase sample rate, disable unused oscillators) to improve responsiveness.
This system is most effective when used as one component within a broader trading methodology that includes sound risk management, multi-timeframe analysis, market context awareness, and disciplined execution. It is a tool for regime detection and signal confirmation, not a substitute for comprehensive trade planning.
Technical Notes
Calculation Timing : All signal logic (ignition, collapse) is evaluated using bar-close values. The barstate.isconfirmed or implicit bar-close behavior ensures signals do not repaint. Visual components (tables, plots) render on every tick for real-time feedback but do not affect signal generation.
Phase Wrapping : Phase angles are calculated in the range -180° to +180° using atan2. Angular distance calculations account for wrapping (e.g., the distance between +170° and -170° is 20°, not 340°). This ensures phase-lock detection works correctly across the ±180° boundary.
Array Management : The indicator uses fixed-size arrays for oscillator phases, amplitudes, and the entanglement matrix. The maximum number of oscillators is 8. If fewer oscillators are enabled, array sizes shrink accordingly (only active oscillators are processed).
Matrix Indexing : The entanglement matrix is stored as a flat array with size N×N, where N is the number of active oscillators. Index mapping: index(row, col) = row × N + col. Symmetric pairs (i,j) and (j,i) are stored identically.
Normalization Stability : Oscillators are normalized to using fixed reference levels (e.g., RSI overbought/oversold at 70/30). For unbounded oscillators (MACD, ROC, TSI), statistical normalization (division by rolling standard deviation) is used, with clamping to prevent extreme outliers from distorting phase calculations.
Smoothing and Lag : The CI smoothing window (SMA) introduces lag proportional to the window size. This is intentional—it filters out single-bar noise spikes in coherence. Users requiring faster reaction can reduce the smoothing window to 1-2 bars, at the cost of increased sensitivity to noise.
Complex Number Representation : Pine Script does not have native complex number types. Complex arithmetic is implemented using separate real and imaginary accumulators (sum_cos, sum_sin) and manual calculation of magnitude (sqrt(real² + imag²)) and argument (atan2(imag, real)).
Lookback Limits : The indicator respects Pine Script's maximum lookback constraints. Historical phase and amplitude values are accessed using the operator, with lookback limited to the chart's available bar history (max_bars_back=5000 declared).
Visual Rendering Performance : Tables (orbit plot, heat map, web, dashboard) are conditionally deleted and recreated on each update using table.delete() and table.new(). This prevents memory leaks but incurs redraw overhead. Rendering is restricted to barstate.islast (last bar) to minimize computational load—historical bars do not render visuals.
Alert Condition Triggers : alertcondition() functions evaluate on bar close when their boolean conditions transition from false to true. Alerts do not fire repeatedly while a condition remains true (e.g., CI stays above threshold for 10 bars fires only once on the initial cross).
Color Gradient Functions : The phaseColor() function maps phase angles to RGB hues using sine waves offset by 120° (red, green, blue channels). This creates a continuous spectrum where -180° to +180° spans the full color wheel. The amplitudeColor() function maps amplitude to grayscale intensity. The coherenceColor() function uses cos(phase) to map contribution to CI (positive = green, negative = red).
No External Data Requests : QRFM operates entirely on the chart's symbol and timeframe. It does not use request.security() or access external data sources. All calculations are self-contained, avoiding lookahead bias from higher-timeframe requests.
Deterministic Behavior : Given identical input parameters and price data, QRFM produces identical outputs. There are no random elements, probabilistic sampling, or time-of-day dependencies.
— Dskyz, Engineering precision. Trading coherence.
Trend Duration Forecast [ChartPrime]⯁ OVERVIEW
The Trend Duration Forecast indicator is designed to estimate the probable lifespan of a bullish or bearish trend. Using a Hull Moving Average (HMA) to detect directional shifts, it tracks the duration of each historical trend and calculates an average to forecast how long the current trend is statistically likely to continue. This allows traders to visualize both real-time trend strength and potential exhaustion zones with exceptional clarity.
⯁ KEY FEATURES
Dynamic Trend Detection: Utilizes the Hull Moving Average to identify when price transitions into a new uptrend or downtrend.
Trend Duration Counting: Measures the number of bars in each completed bullish and bearish phase to understand trend persistence.
Forecast Projection: Automatically projects an estimated trend continuation line based on the average length of recent trends.
Real-Time Updates: Continuously updates the “Real Length” label as the trend develops.
Historical Data Table: Displays previous trend durations for both bullish and bearish cycles, along with their averages.
Adaptive Sampling: Uses a customizable sample size to smooth out volatility in the forecast and provide statistically meaningful projections.
Color-Based Clarity: Highlights uptrends in green and downtrends in orange for instant visual interpretation.
⯁ USAGE
Use the Trend Detection Sensitivity setting to control how fast or slow the indicator reacts to trend changes — lower values increase responsiveness, while higher values smooth out noise.
Compare the Real Length of the ongoing trend with the Probable Length forecast to estimate whether the move is nearing exhaustion.
Observe the historical duration table to understand the average lifespan of trends in the current market structure.
Use the color-coded HMA line and projection arrows to identify when momentum strength is fading and prepare for possible reversals.
Ideal for swing or trend-following strategies where trend longevity is crucial to managing entries and exits effectively.
⯁ CONCLUSION
The Trend Duration Forecast gives traders a quantitative edge by combining real-time trend tracking with statistical forecasting. It helps identify not only when a new trend begins, but also how long it’s likely to persist based on past market behavior. This indicator enhances timing precision for both entries and exits, supporting smarter trend-following decisions with clear, data-driven insights.
ICT Reversals identify when the "top is in " or the bottom is in ,
3 factors to detect if top or bottom is in based on ICT principals:
1. daily High and Daily low of the previous day - the market will reach that point and likely to reverse
2.diviation from Volume at top or bottom compared to the last X candles - default is 9.
3. detection of FVG on the last 4 candles to identify imbalance - stretched price aka distribution
after this the market will either consolidate and then reveres or consolidate and retrace before another leg up - remember retracement is 70% min so its enough to use also on retracement not just reversal.
IT ONLY WORKS ON 4 CHART ATM
Remember WAIT for the FVG to be touched on the bounce before entring !!
GL
MAHAR K Stochastic IndicatorWhat It Does
%K line calculates fast stochastic of _src over length, then re-smoothed twice: sk (smoothK), %D (smoothD), and slower %F (smoothF).
Plots the three lines, draws 80/50/20 bands, and highlights extreme values by drawing red circles when sk hits 100 and green when it hits 0.
Notable Details
sma_signal chooses the smoothing kernel (SMA, EMA, WMA, DEMA). ma() delegates to the selected function and contains a VWMA branch even though VWMA is not listed in the input options.
A custom dema() helper implements the classic double EMA.
stOBOS is always true, so the ternary wrappers around the circle plots can be simplified.
Risk / Edge Cases
If highestHigh == lowestLow (flat price over the window) the %K calculation divides by zero, yielding na. Consider guarding against that or defaulting to previous values.
To actually expose VWMA, add it to the input options; otherwise remove the dead code branch.
Next Steps
Decide whether to safeguard the denominator before plotting.
Align the smoothing options with the available choices and prune the redundant conditionals if desired.
Obj_XABCD_HarmonicLibrary "Obj_XABCD_Harmonic"
Harmonic XABCD Pattern object and associated methods. Easily validate, draw, and get information about harmonic patterns. See example code at the end of the script for details.
init_params(pct_error, pct_asym, types, w_e, w_p, w_d)
Create a harmonic parameters object (used by xabcd_harmonic object for pattern validation and scoring).
Parameters:
pct_error (float) : Allowed % error of leg retracement ratio versus the defined harmonic ratio
pct_asym (float) : Allowed leg length/period asymmetry % (a leg is considered invalid if it is this % longer or shorter than the average length of the other legs)
types (array) : Array of pattern types to validate (1=Gartley, 2=Bat, 3=Butterfly, 4=Crab, 5=Shark, 6=Cypher)
w_e (float) : Weight of ratio % error (used in score calculation, dft = 1)
w_p (float) : Weight of PRZ confluence (used in score calculation, dft = 1)
w_d (float) : Weight of Point D / PRZ confluence (used in score calculation, dft = 1)
Returns: harmonic_params object instance. It is recommended to store and reuse this object for multiple xabcd_harmonic objects rather than creating new params objects unnecessarily.
init(x, a, b, c, d, params, tp, p)
Initialize an xabcd_harmonic object instance from a given set of points
If the pattern is valid, an xabcd_harmonic object instance is returned. If you want to specify your
own validation and scoring parameters, you can do so by passing a harmonic_params object (params).
Or, if you prefer to do your own validation, you can explicitly pass the harmonic pattern type (tp)
and validation will be skipped. You can also pass in an existing xabcd_harmonic instance if you wish
to re-initialize it (e.g. for re-validation and/or re-scoring).
Parameters:
x (point type from dlmysolutions/Pattern/1) : Point X
a (point type from dlmysolutions/Pattern/1) : Point A
b (point type from dlmysolutions/Pattern/1) : Point B
c (point type from dlmysolutions/Pattern/1) : Point C
d (point type from dlmysolutions/Pattern/1) : Point D
params (harmonic_params) : harmonic_params used to validate and score the pattern. Validation will be skipped if a type (tp) is explicitly passed in.
tp (int) : Pattern type
p (xabcd_harmonic) : xabcd_harmonic object instance to initialize (optional, for re-validation/re-scoring)
Returns: xabcd_harmonic object instance if a valid harmonic, else na
init(xX, xY, aX, aY, bX, bY, cX, cY, dX, dY, params, tp, p)
Initialize an xabcd_harmonic object instance from a given set of x and y coordinate values.
If the pattern is valid, an xabcd_harmonic object instance is returned. If you want to specify your
own validation and scoring parameters, you can do so by passing a harmonic_params object (params).
Or, if you prefer to do your own validation, you can explicitly pass the harmonic pattern type (tp)
and validation will be skipped. You can also pass in an existing xabcd_harmonic instance if you wish
to re-initialize it (e.g. for re-validation and/or re-scoring).
Parameters:
xX (int) : Point X bar index (required)
xY (float) : Point X price/level (required)
aX (int) : Point A bar index (required)
aY (float) : Point A price/level (required)
bX (int) : Point B bar index (required)
bY (float) : Point B price/level (required)
cX (int) : Point C bar index (required)
cY (float) : Point C price/level (required)
dX (int) : Point D bar index
dY (float) : Point D price/level
params (harmonic_params) : harmonic_params used to validate and score the pattern. Validation will be skipped if a type (tp) is explicitly passed in.
tp (int) : Pattern type
p (xabcd_harmonic) : xabcd_harmonic object instance to initialize (optional, for re-validation/re-scoring)
Returns: xabcd_harmonic object instance if a valid harmonic, else na
init(pattern, params, tp, p)
Initialize an xabcd_harmonic object instance from a given pattern
If the pattern is valid, an xabcd_harmonic object instance is returned. If you want to specify your
own validation and scoring parameters, you can do so by passing a harmonic_params object (params).
Or, if you prefer to do your own validation, you can explicitly pass the harmonic pattern type (tp)
and validation will be skipped. You can also pass in an existing xabcd_harmonic instance if you wish
to re-initialize it (e.g. for re-validation and/or re-scoring).
Parameters:
pattern (pattern type from dlmysolutions/Pattern/1) : Pattern
params (harmonic_params) : harmonic_params used to validate and score the pattern. Validation will be skipped if a type (tp) is explicitly passed in.
tp (int) : Pattern type
p (xabcd_harmonic) : xabcd_harmonic object instance to initialize (optional, for re-validation/re-scoring)
Returns: xabcd_harmonic object instance if a valid harmonic, else na
method get_name(p)
Get the pattern name
Namespace types: xabcd_harmonic
Parameters:
p (xabcd_harmonic) : Instance of xabcd_harmonic object
Returns: Pattern name (string)
method get_symbol(p)
Get the pattern symbol
Namespace types: xabcd_harmonic
Parameters:
p (xabcd_harmonic) : Instance of xabcd_harmonic object
Returns: Pattern symbol (1 byte string)
method get_pid(p)
Get the Pattern ID. Patterns of the same type with the same coordinates will have the same Pattern ID.
Namespace types: xabcd_harmonic
Parameters:
p (xabcd_harmonic) : Instance of xabcd_harmonic object
Returns: Pattern ID (string)
method set_target(p, target, target_lvl, calc_target)
Set value for a target. Use the calc_target parameter to automatically calculate the target for a specific harmonic ratio.
Namespace types: xabcd_harmonic
Parameters:
p (xabcd_harmonic) : Instance of xabcd_harmonic object
target (int) : Target (1 or 2)
target_lvl (float) : Target price/level (required if calc_target is not specified)
calc_target (string) : Target to auto calculate (required if target is not specified)
Options:
Returns: Target price/level (float)
method erase_pattern(p)
Erase the pattern
Namespace types: xabcd_harmonic
Parameters:
p (xabcd_harmonic) : Instance of xabcd_harmonic object
Returns: p
method draw_pattern(p, clr)
Draw the pattern
Namespace types: xabcd_harmonic
Parameters:
p (xabcd_harmonic) : Instance of xabcd_harmonic object
clr (color)
Returns: Pattern lines
method erase_label(p)
Erase the pattern label
Namespace types: xabcd_harmonic
Parameters:
p (xabcd_harmonic) : Instance of xabcd_harmonic object
Returns: p
method draw_label(p, clr, txt_clr, txt, tooltip)
Draw the pattern label. Default text is the pattern name.
Namespace types: xabcd_harmonic
Parameters:
p (xabcd_harmonic) : Instance of xabcd_harmonic object
clr (color) : Label color
txt_clr (color) : Text color
txt (string) : Label text
tooltip (string) : Tooltip text
Returns: Label
harmonic_params
Validation and scoring parameters for a Harmonic Pattern object (xabcd_harmonic)
Fields:
pct_error (series float) : Allowed % error of leg retracement ratio versus the defined harmonic ratio
pct_asym (series float)
types (array)
w_e (series float)
w_p (series float)
w_d (series float)
xabcd_harmonic
Harmonic Pattern object
Fields:
bull (series bool) : Bullish pattern flag
tp (series int)
x (point type from dlmysolutions/Pattern/1)
a (point type from dlmysolutions/Pattern/1)
b (point type from dlmysolutions/Pattern/1)
c (point type from dlmysolutions/Pattern/1)
d (point type from dlmysolutions/Pattern/1)
r_xb (series float)
re_xb (series float)
r_ac (series float)
re_ac (series float)
r_bd (series float)
re_bd (series float)
r_xd (series float)
re_xd (series float)
score (series float)
score_eAvg (series float)
score_prz (series float)
score_eD (series float)
prz_bN (series float)
prz_bF (series float)
prz_xN (series float)
prz_xF (series float)
t1Hit (series bool) : Target 1 flag
t1 (series float)
t2Hit (series bool)
t2 (series float)
sHit (series bool) : Stop flag
stop (series float) : Stop level
entry (series float) : Entry level
eHit (series bool)
e (point type from dlmysolutions/Pattern/1)
invalid_d (series bool)
pLines (array)
pLabel (series label)
pid (series string)
params (harmonic_params)
PatternLibrary "Pattern"
Pattern object definitions and functions. Easily draw and keep track of patterns, legs, and points.
Supported pattern types:
Type Leg validation # legs
"xabcd" Direction 3 or 4 (point D not required)
"zigzag" Direction >= 2
"free" None >= 2
Summary of exported types and associated methods/functions:
type point A point on the chart (x,y)
draw_label() Draw a point label
erase_label() Erase a point label
type leg A pattern leg (i.e. point A to point B)
leg_init() Initialize/instantiate a leg
draw() Draw a leg
erase() Erase a leg
leg_getLineTerms() Get the slope and y-intercept of a leg
leg_getPrice() Get price (Y) at a given bar index (X) within a leg
type pattern A pattern (set of at least 2 connected legs)
pattern_init() Initialize/instantiate a pattern
draw() Draw a pattern
erase() Erase a pattern
*See bottom of the script for example usage*
erase_label(this)
Delete the point label
Parameters:
this (point) : Point
Returns: Void
draw_label(this, position, clr, transp, txt_clr, txt, tooltip, size)
Draw the point label
Parameters:
this (point) : Point
position (string)
clr (color)
transp (float)
txt_clr (color)
txt (string)
tooltip (string)
size (string)
Returns: line
leg_init(a, b, prev, next, line)
Initialize a pattern leg
Parameters:
a (point) : Point A (required)
b (point) : Point B (required)
prev (leg) : Previous leg
next (leg) : Next leg
line (line) : Line
Returns: New instance of leg object
erase(this)
Delete the pattern leg
Parameters:
this (leg) : Leg
Returns: Void
erase(this)
Delete the pattern lines
Parameters:
this (pattern) : Pattern
Returns: Void
draw(this, clr, style, transp, width)
Draw the pattern leg
Parameters:
this (leg) : Leg
clr (color) : Color
style (string) : Style ("solid", "dotted", "dashed", "arrowleft", "arrowright")
transp (float) : Transparency
width (int) : Width
Returns: line
draw(this, clr, style, transp, width)
Draw the pattern
Parameters:
this (pattern) : Pattern
clr (color) : Color
style (string) : Style ("solid", "dotted", "dashed", "arrowleft", "arrowright")
transp (float) : Transparency
width (int) : Width
Returns: line
leg_getLineTerms(this)
Get the slope and y-intercept of a leg
Parameters:
this (leg) : Leg
Returns:
leg_getPrice(this, index)
Get the price (Y) at a given bar index (X) within the leg
Parameters:
this (leg) : Leg
index (int) : Bar index
Returns: Price (float)
pattern_init(legs, tp, name, subType, pid)
Initialize a pattern object from a given set of legs
Parameters:
legs (array) : Array of pattern legs (required)
tp (string) : Pattern type ("zigzag", "xabcd", or "free". dft = "free")
name (string) : Pattern name
subType (string) : Pattern subtype
pid (string) : Pattern Identifier string
Returns: New instance of pattern object, if one was successfully created
pattern_init(points, tp, name, subType, pid)
Initialize a pattern object from a given set of points
Parameters:
points (array)
tp (string) : Pattern type ("zigzag", "xabcd", or "free". dft = "free")
name (string) : Pattern name
subType (string) : Pattern subtype
pid (string) : Pattern Identifier string
Returns: New instance of pattern object, if one was successfully created
point
A point on the chart (x,y)
Fields:
x (series int) : Bar index (x coordinate)
y (series float)
label (series label)
leg
A pattern leg (point A to point B)
Fields:
a (point) : Point A
b (point)
deltaX (series int)
deltaY (series float)
prev (leg)
next (leg)
retrace (series float)
line (series line)
pattern
A pattern (set of at least 2 connected legs)
Fields:
legs (array)
type (series string)
subType (series string)
name (series string)
pid (series string)
EMA6 or SMA6 Touch AlertThis script monitors the market and notifies you whenever the price touches either the 6-period EMA or the 6-period SMA.
It helps identify potential pullbacks, reaction points, or entry zones, as price interaction with these moving averages often signals short-term market shifts.
What the script does:
Calculates the EMA 6 and SMA 6
Detects if price touches either moving average within the candle
Plots both lines on the chart for visibility
Allows you to set alerts to receive automatic notifications
Best suited for:
Scalping
Day Trading
Pullback Entries
Short-term trend reactions
DrawLibrary "Draw"
Draw patterns, lines, labels, shapes etc.
pat_colors(bull, buLn, beLn, ltxt)
Parameters:
bull (bool)
buLn (color)
beLn (color)
ltxt (color)
size(size)
Parameters:
size (string)
label_style(style)
Parameters:
style (string)
line_style(style)
Parameters:
style (string)
font_size(size)
Parameters:
size (string)
xabcd(xX, xY, aX, aY, bX, bY, cX, cY, dX, dY, iE, bull, bu, be)
Draw XABCD pattern
Parameters:
xX (int)
xY (float)
aX (int)
aY (float)
bX (int)
bY (float)
cX (int)
cY (float)
dX (int)
dY (float)
iE (float)
bull (bool)
bu (color)
be (color)
xabcd_inProgress(bull, type, tLimit, entry, stop, t1, t2, bcNt, bcFt, xaNt, xaFt, xX, xY, aY, bX, bY, cY, dX, dY, cBu, cBe, lTxt)
draw PRZ, entry, stop, targets, and projected reversal paths for XABCD pattern
Parameters:
bull (bool)
type (int)
tLimit (int)
entry (float)
stop (float)
t1 (float)
t2 (float)
bcNt (float)
bcFt (float)
xaNt (float)
xaFt (float)
xX (int)
xY (float)
aY (float)
bX (int)
bY (float)
cY (float)
dX (int)
dY (float)
cBu (color)
cBe (color)
lTxt (color)
xabcd_incInProgress(bull, type, tLimit, entry, xX, xY, aY, bX, bY, cX, cY, dY, cBu, cBe, lTxt)
Parameters:
bull (bool)
type (int)
tLimit (int)
entry (float)
xX (int)
xY (float)
aY (float)
bX (int)
bY (float)
cX (int)
cY (float)
dY (float)
cBu (color)
cBe (color)
lTxt (color)
xabcd_inProgress2(bull, tLimit, entry, stop, t1, t2, xadl, bcdl, xcdl, xX, xY, bX, bY, dX, dY, cBu, cBe, lTxt)
draw PRZ, entry, stop, targets, and projected reversal paths for XABCD pattern
Parameters:
bull (bool)
tLimit (int)
entry (float)
stop (float)
t1 (float)
t2 (float)
xadl (float)
bcdl (float)
xcdl (float)
xX (int)
xY (float)
bX (int)
bY (float)
dX (int)
dY (float)
cBu (color)
cBe (color)
lTxt (color)
eHitLbl(x, e, dX, dY, bull, lOnly)
Draw entry hit label
Parameters:
x (int)
e (float)
dX (int)
dY (float)
bull (bool)
lOnly (bool)
tHitLbl(x, tgt, eX, eY, bull)
Draw target hit label
Parameters:
x (int)
tgt (float)
eX (int)
eY (float)
bull (bool)
sHitLbl(x, s, eX, eY, bull)
Draw stop hit label
Parameters:
x (int)
s (float)
eX (int)
eY (float)
bull (bool)
level(y, x, type, length, extend, padding, b_style, colr, txt_color, txt, txt_loc, txt_size)
Draw a level (box)
Parameters:
y (float)
x (int)
type (int)
length (int)
extend (string)
padding (float)
b_style (string)
colr (color)
txt_color (color)
txt (string)
txt_loc (string)
txt_size (string)
incTtTxt(tp, name, xbr, xbre, acr, acre, bcN, bcF, xaN, xaF, score, e)
Parameters:
tp (int)
name (string)
xbr (float)
xbre (float)
acr (float)
acre (float)
bcN (float)
bcF (float)
xaN (float)
xaF (float)
score (float)
e (float)
TALibrary "TA"
General technical analysis functions
div_bull(pS, iS, cp_length_after, cp_length_before, pivot_length, lookback, lookback_pivs, no_broken, pW, iW, hidW, regW)
Test for bullish divergence
Parameters:
pS (float) : Price series (float)
iS (float) : Indicator series (float)
cp_length_after (simple int) : Bars after current (divergent) pivot low to be considered a valid pivot (optional int)
cp_length_before (simple int) : Bars before current (divergent) pivot low to be considered a valid pivot (optional int)
pivot_length (simple int) : Bars before and after prior pivot low to be considered valid pivot (optional int)
lookback (simple int) : Bars back to search for prior pivot low (optional int)
lookback_pivs (simple int) : Pivots back to search for prior pivot low (optional int)
no_broken (simple bool) : Flag to only consider divergence valid if the pivot-to-pivot trendline is unbroken (optional bool)
pW (simple float) : Weight of change in price, used in degree of divergence calculation (optional float)
iW (simple float) : Weight of change in indicator, used in degree of divergence calculation (optional float)
hidW (simple float) : Weight of hidden divergence, used in degree of divergence calculation (optional float)
regW (simple float) : Weight of regular divergence, used in degree of divergence calculation (optional float)
Returns:
flag = true if divergence exists (bool)
degree = degree (strength) of divergence (float)
type = 1 = regular, 2 = hidden (int)
lx1 = x coordinate 1 (int)
ly1 = y coordinate 1 (float)
lx2 = x coordinate 2 (int)
ly2 = y coordinate 2 (float)
div_bear(pS, iS, cp_length_after, cp_length_before, pivot_length, lookback, lookback_pivs, no_broken, pW, iW, hidW, regW)
Test for bearish divergence
Parameters:
pS (float) : Price series (float)
iS (float) : Indicator series (float)
cp_length_after (simple int) : Bars after current (divergent) pivot high to be considered a valid pivot (optional int)
cp_length_before (simple int) : Bars before current (divergent) pivot highto be considered a valid pivot (optional int)
pivot_length (simple int) : Bars before and after prior pivot high to be considered valid pivot (optional int)
lookback (simple int) : Bars back to search for prior pivot high (optional int)
lookback_pivs (simple int) : Pivots back to search for prior pivot high (optional int)
no_broken (simple bool) : Flag to only consider divergence valid if the pivot-to-pivot trendline is unbroken (optional bool)
pW (simple float) : Weight of change in price, used in degree of divergence calculation (optional float)
iW (simple float) : Weight of change in indicator, used in degree of divergence calculation (optional float)
hidW (simple float) : Weight of hidden divergence, used in degree of divergence calculation (optional float)
regW (simple float) : Weight of regular divergence, used in degree of divergence calculation (optional float)
Returns:
flag = true if divergence exists (bool)
degree = degree (strength) of divergence (float)
type = 1 = regular, 2 = hidden (int)
lx1 = x coordinate 1 (int)
ly1 = y coordinate 1 (float)
lx2 = x coordinate 2 (int)
ly2 = y coordinate 2 (float)
test_cd(cd, bc, xa, xc, ad, pErr, p_types)
Validate CD leg of XABCD
Parameters:
cd (float)
bc (float)
xa (float)
xc (float)
ad (float)
pErr (float)
p_types (array)
pat_xabcd_testSym(xax, abx, bcx, cdx, pAsym)
Validate ΔX symmetry of XABCD pattern
Parameters:
xax (int)
abx (int)
bcx (int)
cdx (int)
pAsym (float)
harmonic_xabcd_validate(xX, xY, aX, aY, bX, bY, cX, cY, dX, dY, pErr, pAsym, gart, bat, bfly, crab, shark, cyph)
Validate harmonic XABCD pattern
Parameters:
xX (int) : X coordinate of point X (int)
xY (float) : Y coordinate of point X (float)
aX (int) : X coordinate of point A (int)
aY (float) : Y coordinate of point A (float)
bX (int) : X coordinate of point B (int)
bY (float) : Y coordinate of point B (float)
cX (int) : X coordinate of point C (int)
cY (float) : Y coordinate of point C (float)
dX (int) : X coordinate of point D (int)
dY (float) : Y coordinate of point D (float)
pErr (float) : Acceptable percent error of leg ratios (does not apply to legs defined within a range) (float)
pAsym (float) : Acceptable percent asymmetry of leg ΔX (each leg tested against average ΔX of prior legs) (float)
gart (bool) : Flag to validate Gartley pattern (bool)
bat (bool) : Flag to validate Bat pattern (bool)
bfly (bool) : Flag to validate Butterfly pattern (bool)
crab (bool) : Flag to validate Crab pattern (bool)
shark (bool) : Flag to validate Shark pattern (bool)
cyph (bool) : Flag to validate Cypher pattern (bool)
Returns:
flag = true if valid harmonic
t1 = true if valid gartley
t2 = true if valid bat
t3 = true if valid butterfly
t4 = true if valid crab
t5 = true if valid shark
t6 = true if valid cypher
harmonic_xabcd_validateIncomplete(xX, xY, aX, aY, bX, bY, cX, cY, pErr, pAsym, gart, bat, bfly, crab, shark, cyph)
Validate the first 3 legs of a harmonic XABCD pattern
Parameters:
xX (int) : X coordinate of point X (int)
xY (float) : Y coordinate of point X (float)
aX (int) : X coordinate of point A (int)
aY (float) : Y coordinate of point A (float)
bX (int) : X coordinate of point B (int)
bY (float) : Y coordinate of point B (float)
cX (int) : X coordinate of point C (int)
cY (float) : Y coordinate of point C (float)
pErr (float) : Acceptable percent error of leg ratios (does not apply to legs defined within a range) (float)
pAsym (float) : Acceptable percent asymmetry of leg ΔX (each leg tested against average ΔX of prior legs) (float)
gart (bool) : Flag to validate Gartley pattern (bool)
bat (bool) : Flag to validate Bat pattern (bool)
bfly (bool) : Flag to validate Butterfly pattern (bool)
crab (bool) : Flag to validate Crab pattern (bool)
shark (bool) : Flag to validate Shark pattern (bool)
cyph (bool) : Flag to validate Cypher pattern (bool)
Returns:
flag = true if valid harmonic
t1 = true if valid gartley
t2 = true if valid bat
t3 = true if valid butterfly
t4 = true if valid crab
t5 = true if valid shark
t6 = true if valid cypher
harmonic_xabcd_prz(type, xY, aY, bY, cY)
Get the potential reversal zone (PRZ) levels of a harmonic XABCD pattern
Parameters:
type (int) : Harmonic pattern type (int - 1 = Gartley, 2 = Bat, 3 = Butterfly, 4 = Crab, 5 = Shark, 6 = Cypher)
xY (float) : Y coordinate of point X (float)
aY (float) : Y coordinate of point A (float)
bY (float) : Y coordinate of point B (float)
cY (float) : Y coordinate of point C (float)
Returns:
bc_u = nearest BC retracement/extension level (nearest to point C)
bc_l = farthest BC retracement/extension level (nearest to point C)
xa_u = nearest XA retracement/extension level (or the only XA level, if applicable)
xa_l = farthest XA retracement/extension level (or na if not applicable)
harmonic_xabcd_przClosest(l1, l2, l3, l4)
Get the confluent PRZ levels (i.e. the two closest PRZ levels)
Order of arguments does not matter
Parameters:
l1 (float) : level 1 (float)
l2 (float) : level 2 (float)
l3 (float) : level 3 (float)
l4 (float) : level 4 (optional, float)
Returns:
lL = lower confluent PRZ level
lH = higher confluent PRZ level
harmonic_xabcd_przRange(l1, l2, l3, l4)
Get upper and lower PRZ levels
Parameters:
l1 (float)
l2 (float)
l3 (float)
l4 (float)
harmonic_xabcd_eD(cpl1, cpl2, xY, aY, dY)
Measure closeness of D to either of the two closest PRZ levels, relative to height of the XA leg
Parameters:
cpl1 (float)
cpl2 (float)
xY (float)
aY (float)
dY (float)
harmonic_xabcd_przScore(xY, aY, l1, l2, l3, l4)
Measure the closeness of the two closest PRZ levels, relative to the height of the XA leg
Parameters:
xY (float)
aY (float)
l1 (float)
l2 (float)
l3 (float)
l4 (float)
harmonic_xabcd_rAndE(type, l, l1, l2)
Get the ratio of two pattern legs, and the percent error from the theoretical harmonic ratio
Order of arguments does not matter
Parameters:
type (int) : Harmonic pattern type (int - 1 = Gartley, 2 = Bat, 3 = Butterfly, 4 = Crab)
l (string) : Leg ID ("xab", "abc", "bcd", or "xad") (string)
l1 (float) : Line 1 height (float)
l2 (float) : Line 2 height (float)
Returns:
harmonic_xabcd_eAvg(xbre, acre, bdre, xdre, xcdre)
Get the avg retracement ratio % error
Parameters:
xbre (float)
acre (float)
bdre (float)
xdre (float)
xcdre (float)
pat_xabcd_asym(xX, aX, bX, cX, dX)
Get the avg asymmetry %
Parameters:
xX (int)
aX (int)
bX (int)
cX (int)
dX (int)
harmonic_xabcd_entry(t, tp, xY, aY, bY, cY, dY, e_afterC, e_lvlc, e_afterD, e_lvldPct)
Get potential entry levels for a harmonic XABCD pattern
Parameters:
t (bool)
tp (int)
xY (float)
aY (float)
bY (float)
cY (float)
dY (float)
e_afterC (bool)
e_lvlc (string)
e_afterD (bool)
e_lvldPct (float)
xabcd_entryHit(t, afterC, afterD, dX, e_afterC, e_afterD, dValBars)
Determine if entry level was reached. Assumes pattern is active/not timed out.
Parameters:
t (bool)
afterC (float)
afterD (float)
dX (int)
e_afterC (bool)
e_afterD (bool)
dValBars (int)
pat_xabcd_validate(xX, xY, aX, aY, bX, bY, cX, cY, dX, dY, xab, abc, bcd, xad, xcd, pErr, pAsym)
Validate custom XABCD pattern
Parameters:
xX (int) : X coordinate of point X (int)
xY (float) : Y coordinate of point X (float)
aX (int) : X coordinate of point A (int)
aY (float) : Y coordinate of point A (float)
bX (int) : X coordinate of point B (int)
bY (float) : Y coordinate of point B (float)
cX (int) : X coordinate of point C (int)
cY (float) : Y coordinate of point C (float)
dX (int) : X coordinate of point D (int)
dY (float) : Y coordinate of point D (float)
xab (float)
abc (float)
bcd (float)
xad (float)
xcd (float)
pErr (float) : Acceptable percent error of leg ratios (does not apply to legs defined within a range) (float)
pAsym (float) : Acceptable percent asymmetry of leg ΔX (each leg tested against average ΔX of prior legs) (float)
Returns: TRUE if pattern is valid
pat_xabcd_validateIncomplete(xX, xY, aX, aY, bX, bY, cX, cY, xab, abc, pErr, pAsym)
Validate the first 3 legs of a custom XABCD pattern
Parameters:
xX (int) : X coordinate of point X (int)
xY (float) : Y coordinate of point X (float)
aX (int) : X coordinate of point A (int)
aY (float) : Y coordinate of point A (float)
bX (int) : X coordinate of point B (int)
bY (float) : Y coordinate of point B (float)
cX (int) : X coordinate of point C (int)
cY (float) : Y coordinate of point C (float)
xab (float)
abc (float)
pErr (float) : Acceptable percent error of leg ratios (does not apply to legs defined within a range) (float)
pAsym (float) : Acceptable percent asymmetry of leg ΔX (each leg tested against average ΔX of prior legs) (float)
Returns: TRUE if first 3 legs are valid
pat_xabcd_prz(xY, aY, bY, cY, xad, bcd, xcd)
Get the potential reversal zone (PRZ) levels of a custom XABCD pattern
Parameters:
xY (float) : Y coordinate of point X (float)
aY (float) : Y coordinate of point A (float)
bY (float) : Y coordinate of point B (float)
cY (float) : Y coordinate of point C (float)
xad (float)
bcd (float)
xcd (float)
Returns:
pat_xabcd_avgDev(xX, xY, aX, aY, bX, bY, cX, cY, dX, dY)
Get the average deviation of an XABCD pattern
Parameters:
xX (int)
xY (float)
aX (int)
aY (float)
bX (int)
bY (float)
cX (int)
cY (float)
dX (int)
dY (float)
harmonic_xabcd_score(tp, xX, xY, aX, aY, bX, bY, cX, cY, dX, dY)
Get score values for a pattern
Parameters:
tp (int)
xX (int)
xY (float)
aX (int)
aY (float)
bX (int)
bY (float)
cX (int)
cY (float)
dX (int)
dY (float)
harmonic_xabcd_scoreTot(asym, eavg, przscore, eD, tp, w_a, w_e, w_p, w_d)
Get total weighted score value for a pattern
Parameters:
asym (float)
eavg (float)
przscore (float)
eD (float)
tp (int)
w_a (float)
w_e (float)
w_p (float)
w_d (float)
harmonic_xabcd_targets(xY, aY, bY, cY, dY, tgt1, tgt2, tgt3)
Get target level
Parameters:
xY (float)
aY (float)
bY (float)
cY (float)
dY (float)
tgt1 (string)
tgt2 (string)
tgt3 (string)
harmonic_xabcd_stop(stop, stopPct, bull, xY, dY, upper, lower, t1, eY)
Get stop level
Parameters:
stop (string)
stopPct (float)
bull (bool)
xY (float)
dY (float)
upper (float)
lower (float)
t1 (float)
eY (float)
harmonic_xabcd_fibDispTxt(tp)
Get fib ratio display text
Parameters:
tp (int)
harmonic_xabcd_symbol(tp)
Get pattern symbol
Parameters:
tp (int)
pat_xabcd(x_is_low, pivot_length, source, conf_length, incomplete)
Determine if an XABCD pattern has just completed (i.e. point D is on the previous bar)
Parameters:
x_is_low (bool) : Flag to determine if point X is a low pivot, i.e. bullish pattern (bool, dft = true)
pivot_length (int) : Number of bars before and after a valid pivot (int, dft = 5)
source (float) : Source series (float, dft = na, will use high and low series)
conf_length (int) : Number of trailing bars after pivot point D to confirm a valid pattern (int, dft = 1)
incomplete (bool) : Flag to return an incomplete XABC pattern (bool, dft = false)
Returns:
flag = true if valid XABCD pattern completed on previous bar
xx = X coordinate of point X (int)
xy = Y coordinate of point X (float)
ax = X coordinate of point A (int)
ay = Y coordinate of point A (float)
bx = X coordinate of point B (int)
by = Y coordinate of point B (float)
cx = X coordinate of point C (int)
cy = Y coordinate of point C (float)
dx = X coordinate of point D (int)
dy = Y coordinate of point D (float)
pat_xabcdIncomplete(x_is_low, pivot_length, source, conf_length)
Determine if an XABCD pattern is in progress (point C was just confirmed)
Parameters:
x_is_low (bool) : Flag to determine if point X is a low pivot, i.e. bullish M pattern (bool, dft = true)
pivot_length (int) : Number of bars before and after a valid pivot (int, dft = 5)
source (float) : Source series (float, dft = na, will use high and low series)
conf_length (int) : Number of trailing bars after pivot point D to confirm a valid pattern (int, dft = 1)
Returns:
flag = true if valid XABC pattern completed on bar_index
xx = X coordinate of point X (int)
xy = Y coordinate of point X (float)
ax = X coordinate of point A (int)
ay = Y coordinate of point A (float)
bx = X coordinate of point B (int)
by = Y coordinate of point B (float)
cx = X coordinate of point C (int)
cy = Y coordinate of point C (float)
dx = X coordinate of point D (int)
dy = Y coordinate of point D (float)
success(eX, stop, t1, t2)
Determine if trade is successful
Parameters:
eX (int) : Entry bar index (int)
stop (float) : Stop level (float)
t1 (float) : Target 1 level (float)
t2 (float) : Target 2 level (float)
Returns:
tradeClosed(eX, eY, stop, t1h, t2h, t1, t2)
Determine if Target or Stop was hit on the current bar
Parameters:
eX (int)
eY (float)
stop (float)
t1h (bool)
t2h (bool)
t1 (float)
t2 (float)
TrigLibrary "Trig"
Trigonometric functions
rt_get_angleAlpha(a, b, c, deg)
Get angle α of a right triangle, given the lengths of its sides
Parameters:
a (float) : length of leg a (float)
b (float) : length of leg b (float)
c (float) : length of hypotenuse (float)
deg (simple bool) : flag to return angle in degrees (bool - default = false)
Returns: angle α in radians (or degrees if deg == true)
rt_get_angleAlphaFromLine(x1, y1, x2, y2, l, deg)
Get angle α of a right triangle formed by the given line
Parameters:
x1 (int) : x coordinate 1 (int - optional, required if argument l is not specified)
y1 (float) : y coordinate 1 (float - optional, required if argument l is not specified)
x2 (int) : x coordinate 2 (int - optional, required if argument l is not specified)
y2 (float) : y coordinate 2 (float - optional, required if argument l is not specified)
l (line) : line object (line - optional, required if x1, y1, x2, and y2 agruments are not specified)
deg (simple bool) : flag to return angle in degrees (bool - default = false)
Returns: angle α in radians (or degrees if deg == true)
rt_get_angleBeta(a, b, c, deg)
Get angle β of a right triangle, given the lengths of its sides
Parameters:
a (float) : length of leg a (float)
b (float) : length of leg b (float)
c (float) : length of hypotenuse (float)
deg (simple bool) : flag to return angle in degrees (bool - default = false)
Returns: angle β in radians (or degrees if deg == true)
rt_get_angleBetaFromLine(x1, y1, x2, y2, l, deg)
Get angle β of a right triangle formed by the given line
Parameters:
x1 (int) : x coordinate 1 (int - optional, required if argument l is not specified)
y1 (float) : y coordinate 1 (float - optional, required if argument l is not specified)
x2 (int) : x coordinate 2 (int - optional, required if argument l is not specified)
y2 (float) : y coordinate 2 (float - optional, required if argument l is not specified)
l (line) : line object (line - optional, required if x1, y1, x2, and y2 agruments are not specified)
deg (simple bool) : flag to return angle in degrees (bool - default = false)
Returns: angle β in radians (or degrees if deg == true)
AlgebraLibrary "Algebra"
line_fromXy(x1, y1, x2, y2)
Get line slope and y-intercept from coordinates
Parameters:
x1 (int) : x coordinate 1 (int - bar index)
y1 (float) : y coordinate 1 (float - price/value)
x2 (int) : x coordinate 2 (int - bar index)
y2 (float) : y coordinate 2 (float - price/value)
Returns: of line
line_getPrice(x, slope, yInt)
Get price at X coordinate, given line slope and y-intercept
Parameters:
x (int) : x coordinate to solve for y (int - bar index)
slope (float) : slope of line (float)
yInt (float) : y-intercept of line (float)
Returns: y (price/value)
line_getPrice_fromXy(x, x1, y1, x2, y2)
Get price at X coordinate, given two points on a line
Parameters:
x (int) : x coordinate to solve for y (int - bar index)
x1 (int) : x coordinate 1 (int - bar index)
y1 (float) : y coordinate 1 (float - price/value)
x2 (int) : x coordinate 2 (int - bar index)
y2 (float) : y coordinate 2 (float - price/value)
Returns: y (price/value)
line_getRtSides(x1, y1, x2, y2, l)
Get length of sides of a right triangle formed by a given line
Parameters:
x1 (int) : x coordinate 1 (int - optional, required if argument l is not specified)
y1 (float) : y coordinate 1 (float - optional, required if argument l is not specified)
x2 (int) : x coordinate 2 (int - optional, required if argument l is not specified)
y2 (float) : y coordinate 2 (float - optional, required if argument l is not specified)
l (line) : line object (line - optional, required if x1, y1, x2, y2 agruments are not specified)
Returns:
line_length(x1, y1, x2, y2, l)
Get length of line, given a line object or two sets of coordinates
Parameters:
x1 (int) : x coordinate 1 (int - optional, required if argument l is not specified)
y1 (float) : y coordinate 1 (float - optional, required if argument l is not specified)
x2 (int) : x coordinate 2 (int - optional, required if argument l is not specified)
y2 (float) : y coordinate 2 (float - optional, required if argument l is not specified)
l (line) : line object (line - optional, required if x1, y1, x2, y2 agruments are not specified)
Returns: length of line (float)
FibonacciLibrary "Fibonacci"
General Fibonacci functions. Get fib numbers, ratios, etc.
fib_derived(f, precision)
Get the precise Fibonacci ratio, to the specified number of decimal places
Parameters:
f (float) : Fibonacci ratio (string, in form #.###)
precision (simple int) : Number of decimal places (optional int, dft = 16, max = 32)
Returns: Precise Fibonacci ratio (float)
* Deprecated (use fib_precise() instead), but keeping it here for science / experimenting with derivations
fib_precise(f, precision)
Get the precise Fibonacci ratio, to the specified number of decimal places
Parameters:
f (float) : Fibonacci ratio (string, in form #.###)
precision (simple int) : Number of decimal places (optional int, dft = 16, max = 16)
Returns: Precise Fibonacci ratio (float)
fib_from_string(r)
Get fib ratio value from string
Parameters:
r (string) : Fib ratio string (e.g. ".618")
Returns: Fibonacci ratio value (float)
fib_n(n)
Calculate the Nth number in the Fibonacci sequence
Parameters:
n (int) : Index/number in sequence (int)
Returns: Fibonacci number (int)
UtilitiesLibrary "Utilities"
General utilities
print_series(s, skip_na, position, show_index, from_index, to_index)
Print series values
Parameters:
s (string) : Series (string)
skip_na (simple bool) : Flag to skip na values (optional bool, dft = false)
position (simple string) : Position to print the Table (optional string, dft = position.bottom_center)
show_index (simple bool) : Flag to show series indices (optional bool, dft = true)
from_index (int) : First index to print (optional int, dft = 0)
to_index (int) : Last index to print (optional int, dft = last_bar_index)
Returns: Table object, if series was printed
print(v, position, at_index)
Print value
Parameters:
v (string) : Value (string)
position (simple string) : Position to print the Table (optional string, dft = position.bottom_center)
at_index (int) : Index at which to print (optional int, dft = bar_index)
Returns: Table object, if value was printed
print(v, position, at_index)
Print value
Parameters:
v (int) : Value (int)
position (simple string) : Position to print the Table (optional string, dft = position.bottom_center)
at_index (int) : Index at which to print (optional int, dft = bar_index)
Returns: Table object, if value was printed
print(v, position, at_index)
Print value
Parameters:
v (float) : Value (float)
position (simple string) : Position to print the Table (optional string, dft = position.bottom_center)
at_index (int) : Index at which to print (optional int, dft = bar_index)
Returns: Table object, if value was printed
print(v, position, at_index)
Print value
Parameters:
v (bool) : Value (bool)
position (simple string) : Position to print the Table (optional string, dft = position.bottom_center)
at_index (int) : Index at which to print (optional int, dft = bar_index)
Returns: Table object, if value was printed
boolToIntArr(a)
return array of offsets (int) of true values
Parameters:
a (array)
intToBoolArr(a, n)
Parameters:
a (array)
n (int)
Buy-Sell Indicator - Michael FernandesThis indicator combines ATR-based trailing stops with EMA crossovers to generate clear buy and sell signals.
It adapts dynamically to market volatility using the Average True Range (ATR) and optionally computes signals from Heikin-Ashi candles for smoother trends.
How It Works:
1. ATR Trailing Stop: Calculates a dynamic stop level above or below price depending on trend direction.
2. EMA Confirmation: A 1-period EMA crossover with the trailing stop helps validate entries.
3. Buy Signal: Triggered when price crosses above the trailing stop and EMA confirms momentum.
4. Sell Signal: Triggered when price crosses below the trailing stop and EMA confirms reversal.
Inputs:
1. Key Value (a): Sensitivity multiplier (higher = tighter stop, more signals).
2. ATR Period (c): Length of ATR used to measure volatility.
3. Heikin-Ashi Mode (h): Option to use smoothed candle data for cleaner trends.
Cyberbikes Adjustable 4x EMA + 4x SMAProbably the best EMA + SMA because you can choose the lenght of 8 different EMA and SMA.
By standard 9,21,80,200 EMA and SMA. Great for tradingview free users, many EMA and SMA in one indicator!
ارتداد من القاع فلتر ارتداد من القاع مع ملاحظة انه يعمل كتنبيه في القائمة
Bottom bounce filter, note that it works as an alert in the menu
KANNADI MOHANRAJA SCALPING 5MINwhen 5 minutes candle color green and 3 min awesome up direction background color green
Swing High/Low (Adaptive)Swing High/Low (Adaptive)
Overview
The Indicator is a pivot point detection tool that identifies swing highs and lows with invalidation tracking. The key differentiator of this indicator is its adaptive invalidation system . Most pivot indicators simply mark every detected pivot without considering whether subsequent price action has made earlier pivots less relevant.
How It Works
The indicator uses Pine Script's native ta.pivotlow() and ta.pivothigh() functions combined with custom logic to detect swing points. The adaptive algorithm evaluates each potential pivot against the following criteria:
For Low Pivots:
Confirms a new low pivot when it's the next expected pivot type in the swing sequence
If consecutive lows occur, only accepts a new low if it's lower than the previous low
Marks the previous low as invalidated when a stronger low is detected
For High Pivots:
Confirms a new high pivot when it's the next expected pivot type in the swing sequence
If consecutive highs occur, only accepts a new high if it's higher than the previous high
Marks the previous high as invalidated when a stronger high is detected
This approach ensures that the indicator maintains clean swing structure and automatically adjusts when price action creates stronger pivots, providing a more realistic view of support and resistance levels.
Settings
Pivot Settings:
Left Bars : Number of bars to the left required for pivot confirmation (default: 5)
Right Bars : Number of bars to the right required for pivot confirmation (default: 5)
Pivot Display Settings:
Toggle visibility for low and high pivots independently
Customizable colors for valid pivot markers
Low pivots marked with upward triangle (▲)
High pivots marked with downward triangle (▼)
Invalid Pivot Settings:
Optional display of invalidated pivots
Separate color customization for invalid low and high pivots
Helps visualize where market structure expectations changed
ZigZag Settings:
Toggle ZigZag line display on/off
Separate colors for upward and downward price swings
Adjustable line width
Use Cases
1. Market Structure Analysis
Identify key swing points to understand the current market structure and trend direction. The adaptive invalidation feature ensures you're always looking at the most relevant pivots.
2. Support and Resistance Identification
Use confirmed swing highs and lows as potential support and resistance levels for entry and exit planning.
3. Trend Confirmation
The ZigZag visualization helps confirm trends by showing the sequence of higher highs and higher lows (uptrend) or lower highs and lower lows (downtrend).
Disclaimer
This indicator is designed as a technical analysis tool and should be used in conjunction with other forms of analysis and proper risk management. Past performance does not guarantee future results, and traders should thoroughly test any strategy before implementing it with real capital.
EMA21 ATR Extension with MetricsThis will show the EMA21 with 0.5 ATR as support. With overbought area 2ATR-2.5ATR. It also has 1.5X daily point
KANNADI MOHANRAJA SCALPINGEach 3minute time frame up direction movement background color goes to green
DA Mark on the wall Well it seems we ran the ball up one more time. i mean Percy is a train , but this thing is insane, Also if you like banter come join the crew discord.gg GREAT channel also free chat
