Trend signal with AlertHello traders,
I updated the Trend signal indicator from @riffster21 () and added alerts to it.
Nothing fancy but still extremely useful
How to use the Trend signal with alerts indicator
In this screenshot, I didn't select the most optimal timeframe, neither the most optimal input for the indicator. I just wanted to explain with a very simple example, how it works and how to use it
Basically, it's being used to simulate obliques trendlines. I draw that one in pink to highligh what is the trendline simulated by the indicator
For Which timeframe ?
It's working for all timeframes.
Recommended input for the indicator ?
The greater the timeframe, the lesser the input should be. Which makes sense because setting a high value period on a weekly chart will give entry/exit signals way too late
On the contrary, on a m5 chart, setting a low value period will give too many fake signals and you'll get angry. I don't want that to happen :)
For crypto intraday trading (meaning m5 to H4), I feel the sweet spot is between 7 and 14 for the indicator input.
For crypto Swing trading (meaning H8 to weekly), an input between 3 and 5 is best
I can only strongly encourage you to apply it on a newly created chart without any other indicator and try to find the best input for the asset. Please note the ideal input might change between assets (example: BTC/USD vs ETH/BTC)
Drawing the corresponding oblique is very important the first time setting them on a chart to find the best setup
Please let me know in the comments section if you have any question
Good luck folks
Dave
Pesquisar nos scripts por "TRENDLINES"
trendline function - JD!EXPERIMENTAL!
As TV doesn't provide a function to draw lines between points, I wrote a function to do this in one my own indicators.
The function itself however can be applied/modified for different use cases, eg. drawing trendlines.
In this (proof of concept) example I used it to draw lines based on past high/low pivot points.
The inputs required:
* an INPUT FUNCTION (in this form, its designed to work with functions that have occasional values and na-values between them, it then connects the non-zero values to form a line)
* a BOOL (to indicate if you want to draw only the rising or falling lines)
* a DELAY (in this case this is the lookback period for the pivot-points function, this is to compensate the calculation of the past and realtime points)
The function returns:
* the function to draw the extension from the BASE-LINE to the current time (here this is the connection of the last pivot-point to the current point to bridge the gap of the lookback period, this is NOT REALTIME!)
* the function to draw the extension for the current time (here this is the continuation of the line until a new pivot-point is valid, this is DRAWN IN REALTIME!!)
* the color of the lines (in this case the lines are only colored (lime or fuchsia) if they either go up or down, else they are invisible, this is to clean up the invalid lines)
these output functions can then simply be plotted using the 'plot' function.
JD.
[LAVA] Relative Price DifferenceThis script shows the relative price difference based off the last high and low, so many bars ago. Bollinger bands are also included by default for closer inspection on the intensity of the movement or the lack thereof. Bollinger bands will follow the smoothed line which will allow the reactionary line to cross the boundary during an intense movement. With the colors selected, a gray color will appear after the color to the zero line to announce a deep correction is possible. Buy/Sell indicators show up as crosses to indicate when the price is moving in a certain direction. Sideways stagnation will have several crosses due to the close proximity to the zero line.
I use 21 in the demo here without the bollinger bands or buy/sell indicators to show the power of the script to identify bottoms and tops using the tips and hand drawn trendlines.
(This script is actually the same script as before, but listed here as the final version. Hopefully this will be my last update with this script.)
If you use and enjoy this script, please like it!
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.
Dynamic EMA Stack Support & ResistanceEvery trader needs reliable support and resistance — but static zones and lagging indicators won't cut it in fast-moving markets. This script combines a Fibonacci-based 5-EMA stacking system and left/right pivots that create dynamic support & resistance logic to uncover real-time structural shifts & momentum zones that actually adapt to price action. This isn’t just a mashup — it’s a complete built-from-the-ground-up support & resistance engine designed for scalpers, intraday traders, and trend followers alike.
🧠 🧠 🧠What It Does🧠 🧠 🧠
This script uses two powerful engines working in sync:
1️⃣ EMA Stack (5-EMA Framework)
Built on Fibonacci-based lengths: 5, 8, 13, 21, 34, (configurable) this stack identifies:
🔹 Bullish Stack: EMAs aligned from fastest to slowest (uptrend confirmation)
🔹 Bearish Stack: EMAs aligned inversely (downtrend confirmation)
🟡 Narrowing Zones: When EMAs compress within ATR thresholds → possible breakout or reversal zone
🎯 Labels identify key transitions like:
✅"Begin Bear Trend?"
✅"Uptrend SPRT"
✅"RES?" (resistance test)
2️⃣ Pivot-Based Projection Engine
Using classic Left/Right Bar pivot logic, the script:
📌 Detects early-stage swing highs/lows before full confirmation
📈 Projects horizontal S/R lines that adapt to market structure
🔁 Keeps lines active until a new pivot replaces them
🧩 Syncs beautifully with EMA stack for confluence zones
🎯🎯🎯Key Features for Traders🎯🎯🎯
✅ Trend Detection
→ EMA order reveals real-time bias (bullish, bearish, compression)
✅ Dynamic S/R Zones
→ Historical support/resistance levels auto-draw and extend
✅ Smart Labeling
→ “SPRT”, “RES”, and “Trend?” labels for live context + testing logic
✅ Custom Candle Coloring
→ Choose from Bar Color or Full Candle Overlay modes
✅ Scalper & Swing Compatible
→ Use fast confirmations for scalping or stack consistency for longer trends
⚙️⚙️⚙️How to Use⚙️⚙️⚙️
✅Use Top/Bottom (trend state) Line Colors to quickly read trend conditions.
✅Use Pivot-based support/resistance projections to anticipate where price might pause or reverse.
✅Watch for yellow/blue zones to prepare for volatility shifts/reversals.
✅Combine with volume or momentum indicators for added confirmation.
📐📐📐Customization Options📐📐📐
✅EMA lengths (5, 8, 13, 21, 34) — fully configurable - try 21,34,55, 89, 144 for longer term trend states
✅Left/Right bar pivot settings (default: 21/5)
✅Label size, visibility, and color themes
✅Toggle line and label visibility for clean layouts
✅“Max Bars Back” to control how deep history is scanned safely
🛠🛠🛠Built-In Safeguards🛠🛠🛠
✅ATR-based filters to stabilize compression logic
✅Guarded lookback (max_bars_back) to avoid runtime errors
✅Works on any asset, any timeframe
🏁🏁🏁Final Word🏁🏁🏁
This script is not just a visual tool, it’s a complete trend and structure framework. Whether you're looking for clean trend alignment, dynamic support/resistance, or early warning labels, this system is tuned to help you react with confidence — not hindsight.
Rembember, no single indicator should be used in isolation. For best results, combine it with price action analysis, higher-timeframe context, and complementary tools like trendlines, moving averages etc Use it as part of a well-rounded trading approach to confirm setups — not to define them alone.
💡💡💡Turn logic into clarity. Structure into trades. And uncertainty into confidence.💡💡💡
Auto Chart PatternsAuto Chart Patterns automatically scans the chart for major technical patterns and marks them directly on price action. It detects:
• Head & Shoulders (bearish reversal)
• Inverse Head & Shoulders (bullish reversal)
• Rising and Falling Wedges
• Double / Triple Tops and Bottoms
• Cup & Handle (bullish continuation)
For each pattern, the script draws the structure (trendlines / neckline), shades the pattern zone, and places a label with the pattern name.
It also generates optional trade signals:
• “BUY” when a bullish pattern breaks out with confirmation
• “SELL” when a bearish pattern breaks down with confirmation
Confirmations can include:
• Follow-through candle in the breakout direction
• Volume spike vs recent average
• RSI momentum agreement
Inputs let you control:
• Pivot sensitivity (left/right bars)
• Pattern types to display
• Cup & Handle depth rules
• Confirmation rules for entry/exit signals
This tool is designed to help you visually spot reversal and continuation setups, highlight potential breakout levels (necklines / wedge boundaries), and time trades with clearer confirmation instead of guessing.
Disclaimer: This script is for educational/technical analysis purposes only. It does not guarantee future performance, does not execute trades, and is not financial advice. Always confirm signals with your own analysis and risk management before entering any position.
FluxVector Liquidity Universal Trendline FluxVector Liquidity Trendline FFTL
Summary in one paragraph
FFTL is a single adaptive trendline for stocks ETFs FX crypto and indices on one minute to daily. It fires only when price action pressure and volatility curvature align. It is original because it fuses a directional liquidity pulse from candle geometry and normalized volume with realized volatility curvature and an impact efficiency term to modulate a Kalman like state without ATR VWAP or moving averages. Add it to a clean chart and use the colored line plus alerts. Shapes can move while a bar is open and settle on close. For conservative alerts select on bar close.
Scope and intent
• Markets. Major FX pairs index futures large cap equities liquid crypto top ETFs
• Timeframes. One minute to daily
• Default demo used in the publication. SPY on 30min
• Purpose. Reduce false flips and chop by gating the line reaction to noise and by using a one bar projection
• Limits. This is a strategy. Orders are simulated on standard candles only
Originality and usefulness
• Unique fusion. Directional Liquidity Pulse plus Volatility Curvature plus Impact Efficiency drives an adaptive gain for a one dimensional state
• Failure mode addressed. One or two shock candles that break ordinary trendlines and saw chop in flat regimes
• Testability. All windows and gains are inputs
• Portable yardstick. Returns use natural log units and range is bar high minus low
• Protected scripts. Not used. Method disclosed plainly here
Method overview in plain language
Base measures
• Return basis. Natural log of close over prior close. Average absolute return over a window is a unit of motion
Components
• Directional Liquidity Pulse DLP. Measures signed participation from body and wick imbalance scaled by normalized volume and variance stabilized
• Volatility Curvature. Second difference of realized volatility from returns highlights expansion or compression
• Impact Efficiency. Price change per unit range and volume boosts gain during efficient moves
• Energy score. Z scores of the above form a single energy that controls the state gain
• One bar projection. Current slope extended by one bar for anticipatory checks
Fusion rule
Weighted sum inside the energy score then logistic mapping to a gain between k min and k max. The state updates toward price plus a small flow push.
Signal rule
• Long suggestion and order when close is below trend and the one bar projection is above the trend
• Short suggestion and flip when close is above trend and the one bar projection is below the trend
• WAIT is implicit when neither condition holds
• In position states end on the opposite condition
What you will see on the chart
• Colored trendline teal for rising red for falling gray for flat
• Optional projection line one bar ahead
• Optional background can be enabled in code
• Alerts on price cross and on slope flips
Inputs with guidance
Setup
• Price source. Close by default
Logic
• Flow window. Typical range 20 to 80. Higher smooths the pulse and reduces flips
• Vol window. Typical range 30 to 120. Higher calms curvature
• Energy window. Typical range 20 to 80. Higher slows regime changes
• Min gain and Max gain. Raise max to react faster. Raise min to keep momentum in chop
UI
• Show 1 bar projection. Colors for up down flat
Properties visible in this publication
• Initial capital 25000
• Base currency USD
• Commission percent 0.03
• Slippage 5
• Default order size method percent of equity value 3%
• Pyramiding 0
• Process orders on close off
• Calc on every tick off
• Recalculate after order is filled off
Realism and responsible publication
• No performance claims
• Intrabar reminder. Shapes can move while a bar forms and settle on close
• Strategy uses standard candles only
Honest limitations and failure modes
• Sudden gaps and thin liquidity can still produce fast flips
• Very quiet regimes reduce contrast. Use larger windows and lower max gain
• Session time uses the exchange time of the chart if you enable any windows later
• Past results never guarantee future outcomes
Open source reuse and credits
• None
J.P. Morgan Efficiente 5 IndexJ.P. MORGAN EFFICIENTE 5 INDEX REPLICATION
Walk into any retail trading forum and you'll find the same scene playing out thousands of times a day: traders huddled over their screens, drawing trendlines on candlestick charts, hunting for the perfect entry signal, convinced that the next RSI crossover will unlock the path to financial freedom. Meanwhile, in the towers of lower Manhattan and the City of London, portfolio managers are doing something entirely different. They're not drawing lines. They're not hunting patterns. They're building fortresses of diversification, wielding mathematical frameworks that have survived decades of market chaos, and most importantly, they're thinking in portfolios while retail thinks in positions.
This divide is not just philosophical. It's structural, mathematical, and ultimately, profitable. The uncomfortable truth that retail traders must confront is this: while you're obsessing over whether the 50-day moving average will cross the 200-day, institutional investors are solving quadratic optimization problems across thirteen asset classes, rebalancing monthly according to Markowitz's Nobel Prize-winning framework, and targeting precise volatility levels that allow them to sleep at night regardless of what the VIX does tomorrow. The game you're playing and the game they're playing share the same field, but the rules are entirely different.
The question, then, is not whether retail traders can access institutional strategies. The question is whether they're willing to fundamentally change how they think about markets. Are you ready to stop painting lines and start building portfolios?
THE INSTITUTIONAL FRAMEWORK: HOW THE PROFESSIONALS ACTUALLY THINK
When Harry Markowitz published "Portfolio Selection" in The Journal of Finance in 1952, he fundamentally altered how sophisticated investors approach markets. His insight was deceptively simple: returns alone mean nothing. Risk-adjusted returns mean everything. For this revelation, he would eventually receive the Nobel Prize in Economics in 1990, and his framework would become the foundation upon which trillions of dollars are managed today (Markowitz, 1952).
Modern Portfolio Theory, as it came to be known, introduced a revolutionary concept: through diversification across imperfectly correlated assets, an investor could reduce portfolio risk without sacrificing expected returns. This wasn't about finding the single best asset. It was about constructing the optimal combination of assets. The mathematics are elegant in their logic: if two assets don't move in perfect lockstep, combining them creates a portfolio whose volatility is lower than the weighted average of the individual volatilities. This "free lunch" of diversification became the bedrock of institutional investment management (Elton et al., 2014).
But here's where retail traders miss the point entirely: this isn't about having ten different stocks instead of one. It's about systematic, mathematically rigorous allocation across asset classes with fundamentally different risk drivers. When equity markets crash, high-quality government bonds often rally. When inflation surges, commodities may provide protection even as stocks and bonds both suffer. When emerging markets are in vogue, developed markets may lag. The professional investor doesn't predict which scenario will unfold. Instead, they position for all of them simultaneously, with weights determined not by gut feeling but by quantitative optimization.
This is what J.P. Morgan Asset Management embedded into their Efficiente Index series. These are not actively managed funds where a portfolio manager makes discretionary calls. They are rules-based, systematic strategies that execute the Markowitz framework in real-time, rebalancing monthly to maintain optimal risk-adjusted positioning across global equities, fixed income, commodities, and defensive assets (J.P. Morgan Asset Management, 2016).
THE EFFICIENTE 5 STRATEGY: DECONSTRUCTING INSTITUTIONAL METHODOLOGY
The Efficiente 5 Index, specifically, targets a 5% annualized volatility. Let that sink in for a moment. While retail traders routinely accept 20%, 30%, or even 50% annual volatility in pursuit of returns, institutional allocators have determined that 5% volatility provides an optimal balance between growth potential and capital preservation. This isn't timidity. It's mathematics. At higher volatility levels, the compounding drag from large drawdowns becomes mathematically punishing. A 50% loss requires a 100% gain just to break even. The institutional solution: constrain volatility at the portfolio level, allowing the power of compounding to work unimpeded (Damodaran, 2008).
The strategy operates across thirteen exchange-traded funds spanning five distinct asset classes: developed equity markets (SPY, IWM, EFA), fixed income across the risk spectrum (TLT, LQD, HYG), emerging markets (EEM, EMB), alternatives (IYR, GSG, GLD), and defensive positioning (TIP, BIL). These aren't arbitrary choices. Each ETF represents a distinct factor exposure, and together they provide access to the primary drivers of global asset returns (Fama and French, 1993).
The methodology, as detailed in replication research by Jungle Rock (2025), follows a precise monthly cadence. At the end of each month, the strategy recalculates expected returns and volatilities for all thirteen assets using a 126-day rolling window. This six-month lookback balances responsiveness to changing market conditions against the noise of short-term fluctuations. The optimization engine then solves for the portfolio weights that maximize expected return subject to the 5% volatility target, with additional constraints to prevent excessive concentration.
These constraints are critical and reveal institutional wisdom that retail traders typically ignore. No single ETF can exceed 20% of the portfolio, except for TIP and BIL which can reach 50% given their defensive nature. At the asset class level, developed equities are capped at 50%, bonds at 50%, emerging markets at 25%, and alternatives at 25%. These aren't arbitrary limits. They're guardrails preventing the optimization from becoming too aggressive during periods when recent performance might suggest concentrating heavily in a single area that's been hot (Jorion, 1992).
After optimization, there's one final step that appears almost trivial but carries profound implications: weights are rounded to the nearest 5%. In a world of fractional shares and algorithmic execution, why round to 5%? The answer reveals institutional practicality over mathematical purity. A portfolio weight of 13.7% and 15.0% are functionally similar in their risk contribution, but the latter is vastly easier to communicate, to monitor, and to execute at scale. When you're managing billions, parsimony matters.
WHY THIS MATTERS FOR RETAIL: THE GAP BETWEEN APPROACH AND EXECUTION
Here's the uncomfortable reality: most retail traders are playing a different game entirely, and they don't even realize it. When a retail trader says "I'm bullish on tech," they buy QQQ and that's their entire technology exposure. When they say "I need some diversification," they buy ten different stocks, often in correlated sectors. This isn't diversification in the Markowitzian sense. It's concentration with extra steps.
The institutional approach represented by the Efficiente 5 is fundamentally different in several ways. First, it's systematic. Emotions don't drive the allocation. The mathematics do. When equities have rallied hard and now represent 55% of the portfolio despite a 50% cap, the system sells equities and buys bonds or alternatives, regardless of how bullish the headlines feel. This forced contrarianism is what retail traders know they should do but rarely execute (Kahneman and Tversky, 1979).
Second, it's forward-looking in its inputs but backward-looking in its process. The strategy doesn't try to predict the next crisis or the next boom. It simply measures what volatility and returns have been recently, assumes the immediate future resembles the immediate past more than it resembles some forecast, and positions accordingly. This humility regarding prediction is perhaps the most institutional characteristic of all.
Third, and most critically, it treats the portfolio as a single organism. Retail traders typically view their holdings as separate positions, each requiring individual management. The institutional approach recognizes that what matters is not whether Position A made money, but whether the portfolio as a whole achieved its risk-adjusted return target. A position can lose money and still be a valuable contributor if it reduced portfolio volatility or provided diversification during stress periods.
THE MATHEMATICAL FOUNDATION: MEAN-VARIANCE OPTIMIZATION IN PRACTICE
At its core, the Efficiente 5 strategy solves a constrained optimization problem each month. In technical terms, this is a quadratic programming problem: maximize expected portfolio return subject to a volatility constraint and position limits. The objective function is straightforward: maximize the weighted sum of expected returns. The constraint is that the weighted sum of variances and covariances must not exceed the volatility target squared (Markowitz, 1959).
The challenge, and this is crucial for understanding the Pine Script implementation, is that solving this problem properly requires calculating a covariance matrix. This 13x13 matrix captures not just the volatility of each asset but the correlation between every pair of assets. Two assets might each have 15% volatility, but if they're negatively correlated, combining them reduces portfolio risk. If they're positively correlated, it doesn't. The covariance matrix encodes these relationships.
True mean-variance optimization requires matrix algebra and quadratic programming solvers. Pine Script, by design, lacks these capabilities. The language doesn't support matrix operations, and certainly doesn't include a QP solver. This creates a fundamental challenge: how do you implement an institutional strategy in a language not designed for institutional mathematics?
The solution implemented here uses a pragmatic approximation. Instead of solving the full covariance problem, the indicator calculates a Sharpe-like ratio for each asset (return divided by volatility) and uses these ratios to determine initial weights. It then applies the individual and asset-class constraints, renormalizes, and produces the final portfolio. This isn't mathematically equivalent to true mean-variance optimization, but it captures the essential spirit: weight assets according to their risk-adjusted return potential, subject to diversification constraints.
For retail implementation, this approximation is likely sufficient. The difference between a theoretically optimal portfolio and a very good approximation is typically modest, and the discipline of systematic rebalancing across asset classes matters far more than the precise weights. Perfect is the enemy of good, and a good approximation executed consistently will outperform a perfect solution that never gets implemented (Arnott et al., 2013).
RETURNS, RISKS, AND THE POWER OF COMPOUNDING
The Efficiente 5 Index has, historically, delivered on its promise of 5% volatility with respectable returns. While past performance never guarantees future results, the framework reveals why low-volatility strategies can be surprisingly powerful. Consider two portfolios: Portfolio A averages 12% returns with 20% volatility, while Portfolio B averages 8% returns with 5% volatility. Which performs better over time?
The arithmetic return favors Portfolio A, but compound returns tell a different story. Portfolio A will experience occasional 20-30% drawdowns. Portfolio B rarely draws down more than 10%. Over a twenty-year horizon, the geometric return (what you actually experience) for Portfolio B may match or exceed Portfolio A, simply because it never gives back massive gains. This is the power of volatility management that retail traders chronically underestimate (Bernstein, 1996).
Moreover, low volatility enables behavioral advantages. When your portfolio draws down 35%, as it might with a high-volatility approach, the psychological pressure to sell at the worst possible time becomes overwhelming. When your maximum drawdown is 12%, as might occur with the Efficiente 5 approach, staying the course is far easier. Behavioral finance research has consistently shown that investor returns lag fund returns primarily due to poor timing decisions driven by emotional responses to volatility (Dalbar, 2020).
The indicator displays not just target and actual portfolio weights, but also tracks total return, portfolio value, and realized volatility. This isn't just data. It's feedback. Retail traders can see, in real-time, whether their actual portfolio volatility matches their target, whether their risk-adjusted returns are improving, and whether their allocation discipline is holding. This transparency transforms abstract concepts into concrete metrics.
WHAT RETAIL TRADERS MUST LEARN: THE MINDSET SHIFT
The path from retail to institutional thinking requires three fundamental shifts. First, stop thinking in positions and start thinking in portfolios. Your question should never be "Should I buy this stock?" but rather "How does this position change my portfolio's expected return and volatility?" If you can't answer that question quantitatively, you're not ready to make the trade.
Second, embrace systematic rebalancing even when it feels wrong. Perhaps especially when it feels wrong. The Efficiente 5 strategy rebalances monthly regardless of market conditions. If equities have surged and now exceed their target weight, the strategy sells equities and buys bonds or alternatives. Every retail trader knows this is what you "should" do, but almost none actually do it. The institutional edge isn't in having better information. It's in having better discipline (Swensen, 2009).
Third, accept that volatility is not your friend. The retail mythology that "higher risk equals higher returns" is true on average across assets, but it's not true for implementation. A 15% return with 30% volatility will compound more slowly than a 12% return with 10% volatility due to the mathematics of return distributions. Institutions figured this out decades ago. Retail is still learning.
The Efficiente 5 replication indicator provides a bridge. It won't solve the problem of prediction no indicator can. But it solves the problem of allocation, which is arguably more important. By implementing institutional methodology in an accessible format, it allows retail traders to see what professional portfolio construction actually looks like, not in theory but in executable code. The the colorful lines that retail traders love to draw, don't disappear. They simply become less central to the process. The portfolio becomes central instead.
IMPLEMENTATION CONSIDERATIONS AND PRACTICAL REALITY
Running this indicator on TradingView provides a dynamic view of how institutional allocation would evolve over time. The labels on each asset class line show current weights, updated continuously as prices change and rebalancing occurs. The dashboard displays the full allocation across all thirteen ETFs, showing both target weights (what the optimization suggests) and actual weights (what the portfolio currently holds after price movements).
Several key insights emerge from watching this process unfold. First, the strategy is not static. Weights change monthly as the optimization recalibrates to recent volatility and returns. What worked last month may not be optimal this month. Second, the strategy is not market-timing. It doesn't try to predict whether stocks will rise or fall. It simply measures recent behavior and positions accordingly. If volatility has risen, the strategy shifts toward defensive assets. If correlations have changed, the diversification benefits adjust.
Third, and perhaps most importantly for retail traders, the strategy demonstrates that sophistication and complexity are not synonyms. The Efficiente 5 methodology is sophisticated in its framework but simple in its execution. There are no exotic derivatives, no complex market-timing rules, no predictions of future scenarios. Just systematic optimization, monthly rebalancing, and discipline. This simplicity is a feature, not a bug.
The indicator also highlights limitations that retail traders must understand. The Pine Script implementation uses an approximation of true mean-variance optimization, as discussed earlier. Transaction costs are not modeled. Slippage is ignored. Tax implications are not considered. These simplifications mean the indicator is educational and analytical, not a fully operational trading system. For actual implementation, traders would need to account for these real-world factors.
Moreover, the strategy requires access to all thirteen ETFs and sufficient capital to hold meaningful positions in each. With 5% as the rounding increment, practical implementation probably requires at least $10,000 to avoid having positions that are too small to matter. The strategy is also explicitly designed for a 5% volatility target, which may be too conservative for younger investors with long time horizons or too aggressive for retirees living off their portfolio. The framework is adaptable, but adaptation requires understanding the trade-offs.
CAN RETAIL TRULY COMPETE WITH INSTITUTIONS?
The honest answer is nuanced. Retail traders will never have the same resources as institutions. They won't have Bloomberg terminals, proprietary research, or armies of analysts. But in portfolio construction, the resource gap matters less than the mindset gap. The mathematics of Markowitz are available to everyone. ETFs provide liquid, low-cost access to institutional-quality building blocks. Computing power is essentially free. The barriers are not technological or financial. They're conceptual.
If a retail trader understands why portfolios matter more than positions, why systematic discipline beats discretionary emotion, and why volatility management enables compounding, they can build portfolios that rival institutional allocation in their elegance and effectiveness. Not in their scale, not in their execution costs, but in their conceptual soundness. The Efficiente 5 framework proves this is possible.
What retail traders must recognize is that competing with institutions doesn't mean day-trading better than their algorithms. It means portfolio-building better than their average client. And that's achievable because most institutional clients, despite having access to the best managers, still make emotional decisions, chase performance, and abandon strategies at the worst possible times. The retail edge isn't in outsmarting professionals. It's in out-disciplining amateurs who happen to have more money.
The J.P. Morgan Efficiente 5 Index Replication indicator serves as both a tool and a teacher. As a tool, it provides a systematic framework for multi-asset allocation based on proven institutional methodology. As a teacher, it demonstrates daily what portfolio thinking actually looks like in practice. The colorful lines remain on the chart, but they're no longer the focus. The portfolio is the focus. The risk-adjusted return is the focus. The systematic discipline is the focus.
Stop painting lines. Start building portfolios. The institutions have been doing it for seventy years. It's time retail caught up.
REFERENCES
Arnott, R. D., Hsu, J., & Moore, P. (2013). Fundamental Indexation. Financial Analysts Journal, 61(2), 83-99.
Bernstein, W. J. (1996). The Intelligent Asset Allocator. New York: McGraw-Hill.
Dalbar, Inc. (2020). Quantitative Analysis of Investor Behavior. Boston: Dalbar.
Damodaran, A. (2008). Strategic Risk Taking: A Framework for Risk Management. Upper Saddle River: Pearson Education.
Elton, E. J., Gruber, M. J., Brown, S. J., & Goetzmann, W. N. (2014). Modern Portfolio Theory and Investment Analysis (9th ed.). Hoboken: John Wiley & Sons.
Fama, E. F., & French, K. R. (1993). Common risk factors in the returns on stocks and bonds. Journal of Financial Economics, 33(1), 3-56.
Jorion, P. (1992). Portfolio optimization in practice. Financial Analysts Journal, 48(1), 68-74.
J.P. Morgan Asset Management. (2016). Guide to the Markets. New York: J.P. Morgan.
Jungle Rock. (2025). Institutional Asset Allocation meets the Efficient Frontier: Replicating the JPMorgan Efficiente 5 Strategy. Working Paper.
Kahneman, D., & Tversky, A. (1979). Prospect Theory: An Analysis of Decision under Risk. Econometrica, 47(2), 263-291.
Markowitz, H. (1952). Portfolio Selection. The Journal of Finance, 7(1), 77-91.
Markowitz, H. (1959). Portfolio Selection: Efficient Diversification of Investments. New York: John Wiley & Sons.
Swensen, D. F. (2009). Pioneering Portfolio Management: An Unconventional Approach to Institutional Investment. New York: Free Press.
EDGAR Daily Overview (EDO)EDGAR Daily Overview (EDO) is a professional all-in-one market guide that helps traders identify where price is likely to move — no more guessing.
The indicator automatically detects key daily base, support (S1–S3), and resistance (R1–R3) levels, allowing you to instantly see potential bounce, rejection, or breakout zones.
Combined with advanced tools such as trendlines, Ichimoku Cloud, MACD, RSI, and Volume Strength, EDO gives you a full real-time picture of the market’s current direction.
Whether you trade intraday or short-term swings, this tool helps you understand where the market is heading today — empowering you to plan precise entries, take profits, and manage risk effectively.
🔒 Invite-Only Script – exclusive access for authorized users only.
CCT Gold Synthetic Market Cap🌎 Gold Synthetic Market Cap
Overview
The Gold Synthetic Market Cap indicator transforms the Gold Spot price (XAU/USD) into a synthetic market capitalization chart, allowing traders and analysts to visualize gold’s total estimated valuation as a global asset — similar to how cryptocurrencies are evaluated by total market cap.
This tool uses the current XAU/USD price multiplied by the total amount of gold ever mined (~210,000 metric tons), automatically converting the result into trillions of US dollars (USD T).
The outcome is a precise and dynamic representation of gold’s real-time market value — displayed as full OHLC candles in a separate chart panel.
🧠 Core Concept
Gold’s price per ounce doesn’t tell the full story of its global valuation.
By converting it to market capitalization, we can compare it to other asset classes such as:
Bitcoin’s total market cap (CRYPTOCAP:BTC)
Global equities and ETFs
Precious metals or commodities benchmarks
This indicator bridges the gap between price analysis and macro asset valuation, offering a quantitative visualization of gold’s total monetary footprint.
⚙️ Technical Mechanics
Base Symbol: OANDA:XAUUSD (or any gold pair available on your chart)
Conversion Constant:
210,000 tons × 32,150.7 oz/ton = 6.76 × 10⁹ ounces
Calculation:
MarketCap = (XAUUSD × total_ounces) / 1e12
Displayed Units: Trillions of USD (USD T)
Chart Type: Full OHLC candles (plotcandle)
Each candle represents the daily/weekly/monthly change in gold’s total market value.
🎛️ User Controls (Inputs)
Toggle Function
Show Average Line? Displays a 21-period SMA (in trillions) for trend-following analysis.
Show Info Table? Adds a small info table at the bottom-right corner showing the current market cap value.
Show Market Cap Label? Displays a live label above the last candle showing the latest market cap value.
Normalize Scale? Adjusts scaling for better visual fit. Leave enabled to avoid flat or off-screen candles.
📈 How to Use
1 - Add the indicator to your Gold Spot chart (XAUUSD).
2 - When added, TradingView automatically creates a separate panel below the main price chart.
3 - You can hide the original XAUUSD chart to focus solely on the synthetic market cap.
4 - Maximize the indicator panel (double-click or use the arrow icon) to view the synthetic market cap in full-screen mode.
Apply any drawing tools, trendlines, or visual overlays directly on this panel (they won’t affect the base chart).
Optionally, compare it side by side with Bitcoin Market Cap (CRYPTOCAP:BTC) for macro-level correlation studies.
🪙 Practical Applications
Compare Gold’s global valuation to Bitcoin, equities, or global M2 supply.
Analyze macro rotation trends between risk-off and risk-on assets.
Estimate how much capital is stored in physical gold versus digital assets.
Integrate into broader multi-asset dashboards for portfolio allocation analysis.
💡 Suggested Workflow
Keep the normalize toggle enabled (default).
Maximize the lower panel for a full synthetic chart view.
Combine this tool with the F!72 SuperTrade or MarketMonitor indicators for contextual macro insight.
Use a weekly or monthly timeframe for clearer long-term structure visualization.
📊 Notes
This indicator uses public XAU/USD pricing and does not require any external API.
Works seamlessly with any TradingView theme (light or dark).
Best viewed with logarithmic scale off, as values are already represented in trillions.
Compatible with all resolutions and broker feeds that support XAUUSD.
🔬 Example Interpretation
If Gold trades around $4,000/oz,
the total market cap is approximately:
4,000 × 32,150.7 × 210,000 ≈ 27 Trillion USD
If Gold rises to $5,000/oz,
the global valuation crosses 33.9 Trillion USD —
a move equivalent to adding the entire market cap of all major tech stocks combined.
🧭 Final Recommendation
This script is designed as an analytical overlay, not a trading signal tool.
It complements technical analysis by providing macro context — showing where gold stands as a global store of value in relation to other capital markets.
For best experience:
Use higher timeframes (1W or 1M)
Maximize the indicator panel
Keep Normalize Scale = ON
⚠️ Disclaimer
This indicator is a visualization and educational tool.
It does not provide financial advice or investment recommendations.
Always perform your own research before making financial decisions.
Author: Central Crypto Traders
Version: 1.0 (October 2025)
Type: Informational Overlay
License: Open for personal and educational use
DAMMU SWING TRADING PROScalping and swing trading tool for 15-min and 1-min charts.
Designed for trend, pullback, and reversal analysis.
Works optionally with Heikin Ashi candles.
Indicators Used
EMAs:
EMA89/EMA75 (green)
EMA200/EMA180 (blue)
EMA633/EMA540 (black)
EMA5-12 channel & EMA12-36 ribbon for short-term trends
Price Action Channel (PAC) – EMA high/low/close, length adjustable
Fractals & Pristine Fractals (BW filter)
Higher High (HH), Lower High (LH), Higher Low (HL), Lower Low (LL) detection
Pivot Points – optional, disables fractals automatically
Bar color coding based on PAC:
Blue → Close above PAC
Red → Close below PAC
Gray → Close inside PAC
Trading Signals
PAC swing alerts: arrows or shapes when price exits PAC with optional 200 EMA filter.
RSI 14 signals (if added):
≥50 → BUY
<50 → SELL
Chart Setup
Two panes: 15-min (trend anchor) + 1-min (entry)
Optional Heikin Ashi candles
Use Sweetspot Gold2 for support/resistance “00” and “0” lines
Trendlines can be drawn using HH/LL or Pivot points
Usage Notes
Trade long only if price above EMA200; short only if below EMA200
Pullback into EMA channels/ribbons signals potential continuation
Fractals or pivot points help define trend reversals
PAC + EMA36 used for strong momentum confirmation
Alerts
Up/Down PAC exit alerts configurable with big arrows or labels
RSI labels show buy/sell zones (optional)
Works on both 15-min and 1-min timeframes
If you want, I can make an even shorter “super cheat-sheet” version for 1-page quick reference for trading. It will list only inputs, signals, and colors.
DAMMU Swing Trading PRODammu Scalping Pro – Short Notes
1️⃣ Purpose:
Scalping and swing trading tool for 15-min and 1-min charts.
Designed for trend continuation, pullbacks, and reversals.
Works well with Heikin Ashi candles (optional).
2️⃣ Core Components:
EMAs:
Fast: EMA5-12
Medium: EMA12-36 Ribbon
Long: EMA75/89 (1-min), EMA180/200 (15-min), EMA540/633
Price Action Channel (PAC): EMA-based High, Low, Close channel.
Fractals: Regular & filtered (BW) fractals for swing recognition.
Higher Highs / Lower Highs / Higher Lows / Lower Lows (HH, LH, HL, LL).
Pivot Points: Optional display with labels.
3️⃣ Bar Coloring:
Blue: Close above PAC
Red: Close below PAC
Gray: Close inside PAC
4️⃣ Alerts:
Swing Buy/Sell arrows based on PAC breakout and EMA200 filter.
Optional “Big Arrows” mode for visibility.
Alert messages: "SWING_UP" and "SWING_DN"
5️⃣ Workflow / Usage Tips:
Set chart to 15-min (for trend) + 1-min (for entry).
Optionally enable Heikin Ashi candles.
Trade long only above EMA200, short only below EMA200.
Watch for pullbacks into EMA channels or ribbons.
Confirm trend resumption via PAC breakout & bar color change.
Use fractals and pivot points to draw trendlines and locate support/resistance.
6️⃣ Optional Filters:
Filter PAC signals with 200 EMA.
Filter fractals for “Pristine/Ideal” patterns (BW filter).
7️⃣ Visuals:
EMA ribbons, PAC fill, HH/LL squares, fractal triangles.
Pivot labels & candle numbering for patterns.
8️⃣ Notes:
No extra indicators needed except optionally SweetSpot Gold2 for major S/R levels.
Suitable for scalping pullbacks with trend confirmation.
If you want, I can make an even shorter “one-screen cheat sheet” with colors, alerts, and EMAs, perfect for real-time chart reference.
Do you want me to do that?
DAMMU Swing Trading PRODammu Scalping Pro – Short Notes
1️⃣ Purpose:
Scalping and swing trading tool for 15-min and 1-min charts.
Designed for trend continuation, pullbacks, and reversals.
Works well with Heikin Ashi candles (optional).
2️⃣ Core Components:
EMAs:
Fast: EMA5-12
Medium: EMA12-36 Ribbon
Long: EMA75/89 (1-min), EMA180/200 (15-min), EMA540/633
Price Action Channel (PAC): EMA-based High, Low, Close channel.
Fractals: Regular & filtered (BW) fractals for swing recognition.
Higher Highs / Lower Highs / Higher Lows / Lower Lows (HH, LH, HL, LL).
Pivot Points: Optional display with labels.
3️⃣ Bar Coloring:
Blue: Close above PAC
Red: Close below PAC
Gray: Close inside PAC
4️⃣ Alerts:
Swing Buy/Sell arrows based on PAC breakout and EMA200 filter.
Optional “Big Arrows” mode for visibility.
Alert messages: "SWING_UP" and "SWING_DN"
5️⃣ Workflow / Usage Tips:
Set chart to 15-min (for trend) + 1-min (for entry).
Optionally enable Heikin Ashi candles.
Trade long only above EMA200, short only below EMA200.
Watch for pullbacks into EMA channels or ribbons.
Confirm trend resumption via PAC breakout & bar color change.
Use fractals and pivot points to draw trendlines and locate support/resistance.
6️⃣ Optional Filters:
Filter PAC signals with 200 EMA.
Filter fractals for “Pristine/Ideal” patterns (BW filter).
7️⃣ Visuals:
EMA ribbons, PAC fill, HH/LL squares, fractal triangles.
Pivot labels & candle numbering for patterns.
8️⃣ Notes:
No extra indicators needed except optionally SweetSpot Gold2 for major S/R levels.
Suitable for scalping pullbacks with trend confirmation.
If you want, I can make an even shorter “one-screen cheat sheet” with colors, alerts, and EMAs, perfect for real-time charT
MACD Pro - Multi-Filter Smart Divergence System# MACD Pro - Multi-Filter Smart Divergence System
## Professional MACD with Advanced Filtering & Automatic Divergence Detection
Transform the classic MACD indicator with professional-grade filters, automated divergence detection, and pre-optimized profiles for different markets.
---
## KEY FEATURES
### Smart Signal Filtering
- **Zero-Line Territory Filter** - Eliminates weak crossovers
- **3-Period Confirmation** - Reduces false signals
- **Minimum Distance Threshold** - Filters out noise
- **Multi-Indicator Confirmation** - RSI + Volume validation
### Automatic Divergence Detection
- **Visual Divergence Lines** - Connects price and MACD pivots automatically
- **Bullish/Bearish Recognition** - Real-time identification
- **Customizable Lookback** - Adjust sensitivity
- **Clean Display** - Managed line limits
### Pre-Optimized Market Profiles
- **S&P 500** (2/60/2) - Tested +3.63% annual
- **Gold** (14/48/3) - Optimized for volatility
- **Forex 30m** (24/52/9) - 24/7 market adapted
- **Scalping 1m** (5/13/6) - Quick trades
- **Linda Raschke** (3/10/16) - Classic scalping
- **Swing Trading** (8/24/9) - Higher timeframes
### Advanced Technical Features
- **ATR Normalization** - Volatility adaptation
- **Predictive Forecast** - Linear regression projection
- **Multi-Timeframe View** - Higher TF overlay
- **Volume Analysis** - Spike confirmation
- **Professional Dashboard** - Real-time metrics
---
## HOW TO USE
**Quick Start:**
1. Enable "Use Optimized Profile"
2. Select your market type
3. Watch for signal arrows and divergence lines
4. Confirm with dashboard metrics
**Signal Types:**
- 🔺 Green Triangle = Bullish crossover (filtered)
- 🔻 Red Triangle = Bearish crossover (filtered)
- ⚪ Small Circle = Conservative zero-line cross
- 🟢 Green Line = Bullish divergence
- 🔴 Red Line = Bearish divergence
---
## CUSTOMIZATION
**Filters:** Toggle each filter independently for your risk tolerance
**Divergence:** Adjust lookback period, line width, and maximum displayed lines
**Confirmation:** Customize RSI levels and volume spike thresholds
**Display:** Choose histogram, forecast, and multi-timeframe options
---
## ALERT CONDITIONS
- MACD Long Signal
- MACD Short Signal
- Bullish Divergence
- Bearish Divergence
---
## IMPORTANT NOTES
**Repainting:** Divergence detection uses historical pivots and may redraw. Crossover signals are non-repainting.
**Disclaimer:** Pre-optimized profiles based on historical data. Past performance does not guarantee future results. This indicator is for educational purposes only, not financial advice.
---
## BEST PRACTICES
**Timeframes:**
- 1-5m → Scalping profile
- 15-30m → Forex profile
- 1-4h → Swing profile
- Daily → S&P 500/Gold profiles
**Market Conditions:**
- Trending → Focus on momentum
- Ranging → Enable all filters, watch divergences
- Volatile → Use ATR normalization
**Combine With:** Support/resistance levels, trendlines, moving averages, and price action analysis.
---
## WHY MACD PRO?
| Feature | Standard MACD | MACD Pro |
|---------|--------------|----------|
| Signal Filters | ❌ | ✅ 5 Advanced |
| Divergence | ❌ Manual | ✅ Automatic |
| Market Profiles | ❌ | ✅ 7 Optimized |
| Volume Filter | ❌ | ✅ Built-in |
| Multi-Timeframe | ❌ | ✅ Yes |
| ATR Adaptation | ❌ | ✅ Yes |
---
**If you find this indicator useful, please boost 🚀**
*Protected source code. Compatible with all TradingView plans.*
Dual RSI TL (AI Trend Mapper) - SigmorAlgoDual RSI TL (AI Trend Mapper) — an intelligent momentum and trendline mapping system built to give traders clarity, structure, and precision.
It merges a dual-layer RSI framework (fast & slow) with automatic RSI trendlines to identify strength, exhaustion, and reversals in real time.
⚙️ Main Features:
• Dual RSI system (fast & slow) with fully adjustable lengths
• Automatic RSI trendline mapping (AI-driven slope detection)
• Real-time crossover and confirmation alerts
• Clean visual markers for entry & exit points
• Compatible with EMA, SMA, and Pivot-based systems
💡 Recommended Settings:
• Default: Fast = 25, Slow = 75 (1:3 ratio) — ideal balance for 15m–1D traders
• Faster reaction: 12/36 or 14/42
• Slower/long-term: 28/84 or 30/90
Whether you trade scalps, intraday setups, or daily swings, Dual RSI TL adapts dynamically to price behavior — giving you a visual edge without noise.
Created by SigmorAlgo — for traders who value clarity over clutter.
EquiSense AI Signals🇸🇦 العربي
المتنبئ الذكي المتوازن (AI v7)
وصف قصير:
مؤشر تجميعي ذكي يوازن بين الاتجاه والزخم والحجم والتذبذب وأنماط الشموع، ويحوّلها إلى نظام نقاط ونجوم يولّد إشارات شراء/بيع مؤكَّدة بتقاطع MACD. بعد الإشارة، يعرض أهدافًا ذكية (TP1/TP2/TP3) ووقف خسارة مبنيَّيْن على ATR مع رسومات مستقبلية ولوحة معلومات لإدارة الصفقة.
الإعدادات (Inputs)
الحد الأدنى للنقاط (min_score): افتراضي 6.0 — كلما ارتفع قلّت الإشارات وزادت جودتها.
الحد الأدنى للنجوم (min_stars): افتراضي 2 — فلتر لقوة الإشارة.
عدد الشموع المستقبلية (future_bars): افتراضي 15 — مدى رسم الأهداف والوقف للأمام.
استخدام الأهداف الذكية (use_ai_targets): تفعيل/إيقاف مضاعِف الذكاء الاصطناعي للأهداف والوقف.
كيف يعمل؟
يحسب المؤشر buy_score/sell_score من مجموعة عوامل: EMA8/21/50/200، RSI + متوسطه، MACD + Histogram، Stochastic، ADX/DMI، VWAP، الحجم، MTF 15m، ROC/المومنتَم، Heikin Ashi، وأنماط (ابتلاع/مطرقة/شهاب).
يحوّل الدرجات إلى نجوم (⭐⭐ إلى ⭐⭐⭐⭐⭐) حسب القوة.
تولّد الإشارة فقط إذا توفّر: درجة ≥ الحد + نجوم ≥ الحد + تقاطع MACD (صعودًا للشراء، هبوطًا للبيع).
عند الإشارة يبدأ سيناريو صفقة واحدة فقط حتى تنتهي (TP3 أو SL).
الأهداف والوقف (ذكاء اصطناعي)
تُشتق من ATR ثم تُعدَّل عبر مضاعِف AI مبني على: ATR%، الزخم (ROC)، الحجم مقابل متوسطه، قوة الاتجاه (ADX)، وعدد النجوم.
تقريبيًا:
TP1 ≈ 1.5×ATR × AI
TP2 ≈ 2.5×ATR × AI
TP3 ≈ 4.0×ATR × AI
SL ≈ 1.0×ATR ÷ AI
ماذا سترى على الشارت؟
علامات “شراء/بيع”، نجوم قرب الإشارة، خط دخول (أزرق)، وقف (أحمر منقّط)، TP1/TP2 (أخضر)، TP3 (ذهبي) مع صناديق مناطق للأهداف وخط ربط نحو الهدف النهائي.
وسم AI يعرض نسبة المضاعِف والنجوم بصريًا.
لوحة معلومات تعرض الحالة، القوة، AI%، السعر، الدرجات، وأثناء الصفقة: الدخول، TP1/TP2/TP3، والربح اللحظي.
التنبيهات (Alerts)
شرطان جاهزان: شراء وبيع عند تحقق الإشارة.
أضِف تنبيه: Right click → Add alert → اختر المؤشر → الشرط المطلوب.
أفضل الممارسات
استخدم الإطار المناسب للأصل:
سكالبينغ 5–15m: min_score 8 وmin_stars 3–4.
تأرجحي H1–H4: min_score 7 وmin_stars 3.
يومي/أسهم: min_score 6–7 وmin_stars 2–3.
فضّل التداول مع EMA200 واتجاه MTF 15m.
خفّض المخاطرة وقت الأخبار العالية.
التزم بإدارة مخاطر ثابتة (مثلاً 1% لكل صفقة).
حدود مهمة
الأفضل انتظار إغلاق الشمعة لتأكيد التقاطعات وتجنّب تغيّرها.
صفقة واحدة في المرة بفضل حالة in_trade.
يستخدم request.security مع lookahead_off لإطار 15m؛ التزم بالتقييم عند الإغلاق.
أسئلة شائعة
هل يستخدم منفردًا؟ نعم، لكن مع مناطق سعرية/ترند وخطة مخاطر يصبح أقوى.
لماذا تختلف الأهداف؟ لأن مضاعِف AI يكيّف TP/SL مع ظروف السوق.
إخلاء مسؤولية
هذه أداة تحليلية تعليمية وليست نصيحة استثمارية. اختبر الإعدادات تاريخيًا والتزم بالمخاطرة المناسبة.
ملاحظة للمبرمجين
Pine Script v6، متغيرات var لحفظ الحالة، تنظيف الرسومات على الشمعة الأخيرة، مع حدود مرتفعة للرسوم لتجنّب الأخطاء.
🇬🇧 English
Balanced Smart Predictor (AI v7)
Short description:
A smart, ensemble-style indicator that blends trend, momentum, volume, volatility, and candle patterns into a score & star system that produces Buy/Sell signals confirmed by MACD crosses. After a signal, it projects smart targets (TP1/TP2/TP3) and a stop-loss derived from ATR, with forward drawings and a control panel for trade management.
Inputs
Minimum Score (min_score): default 6.0 — higher = fewer but stronger signals.
Minimum Stars (min_stars): default 2 — extra filter for strength.
Future Bars (future_bars): default 15 — how far targets/SL are drawn ahead.
Use AI Targets (use_ai_targets): toggle the AI multiplier for TP/SL.
How it works
Computes buy_score/sell_score from: EMA8/21/50/200, RSI & its MA, MACD & Histogram, Stochastic, ADX/DMI, VWAP, Volume, 15m MTF tilt, ROC/Momentum, Heikin Ashi, and candle patterns (engulfing/hammer/shooting star).
Converts scores into Stars (⭐⭐ to ⭐⭐⭐⭐⭐) via tiered thresholds.
Signals fire only when: Score ≥ minimum + Stars ≥ minimum + MACD cross (up = Buy, down = Sell).
On a signal, one active trade is managed until TP3 or SL is reached.
Targets & Stop (AI-driven)
Targets and SL are ATR-based, then adjusted by an AI multiplier derived from: ATR%, momentum (ROC), relative volume, trend strength (ADX), and star rating.
Approximate formulas:
TP1 ≈ 1.5×ATR × AI
TP2 ≈ 2.5×ATR × AI
TP3 ≈ 4.0×ATR × AI
SL ≈ 1.0×ATR ÷ AI
What you’ll see on chart
“Buy/Sell” markers with small Star labels, an Entry line (blue), SL (red dotted), TP1/TP2 (green), TP3 (gold) with shaded target boxes and a guide line towards the final target.
A central AI badge showing the multiplier % and star rating.
A top-right Panel showing status, strength, AI%, price, scores, and during trades: entry, TP1/TP2/TP3, and live P/L.
Alerts
Two ready-made conditions: Buy and Sell when the respective signal triggers.
Add alert: Right click → Add alert → choose the indicator → select condition.
Best practices
Match timeframe to instrument:
Scalping 5–15m: min_score 8, min_stars 3–4.
Swing H1–H4: min_score 7, min_stars 3.
Daily/Equities: min_score 6–7, min_stars 2–3.
Prefer trades with EMA200 and 15m MTF trend alignment.
De-risk around major news.
Use fixed risk per trade (e.g., 1%).
Important notes
Prefer bar close confirmation to avoid mid-bar MACD flips.
Single trade at a time via the in_trade state.
15m MTF uses request.security with lookahead_off; evaluate at close for consistency.
FAQ
Use it standalone? You can, but it’s stronger when combined with S/R zones/trendlines and solid risk management.
Why do targets vary? The AI multiplier adapts TP/SL to current market conditions.
Disclaimer
This is an analytical/educational tool, not financial advice. Always backtest and use appropriate risk management.
Developer note
Built in Pine Script v6, uses var for trade state, clears drawings on the last bar to keep the chart tidy, and raises drawing limits to avoid runtime errors.
Institutional RSI Trendline Breakout StrategyKey Features:
1. RSI Trendline Detection
Automatically identifies RSI resistance (bearish) and support (bullish) trendlines
Requires minimum touch points for validation
Dynamic trendline calculation with configurable pivot lookback
2. Market Structure Analysis
Detects swing highs/lows to identify uptrends and downtrends
Combines multiple trend confirmation methods (swing structure + moving averages)
Visual background highlighting for trend confirmation
3. Breakout Signals
Buy Signal: RSI breaks above resistance trendline + bullish market structure
Sell Signal: RSI breaks below support trendline + bearish market structure
Configurable breakout threshold to avoid false signals
4. ATR-Based Stop Loss
Dynamic stop loss placement based on market volatility
Multiplier-adjustable for different risk profiles
Visual plotting of stop loss levels
5. Signal Filters
Volume filter to confirm breakout validity
RSI level filters to avoid extreme conditions
Multiple validation layers for institutional-grade accuracy
6. Professional Visualization
Clear buy/sell signal markers on chart
Information dashboard with real-time metrics
Trend background highlighting
Stop loss level indicators
7. Alert System
Ready-to-use alerts for both buy and sell signals
Includes entry price and stop loss in alert messages
This script provides institutional-grade signal quality with multiple confirmation layers, optimal risk management, and comprehensive market analysis.
50% Fib Trend Cloud + ATR BandsThis indicator plots two structural 50% fibonacci midpoints from recent confirmed 'left/right' swings that form a *cloud* of equilibrium, then adds a rolling 50% fibonacci range midpoint based on a lookback window that's wrapped in ATR bands. Importantly, it solves a specific trading problem:
Structural midpoints (macro context) are powerful but can lag when price escapes prior ranges. Enter rolling 50% fib + ATR ➡️ which restores real-time balance & tolerance (micro context). Together they show where price is balanced structurally, where it’s balanced right now, and how much volatility to tolerate before acting.
➖➖➖
🔑 Why this is different
Most tools either draw a single midpoint (ex., daily 50%) or ATR bands around a moving average. This script fuses dual swing-based 50% midpoints (structure) + a rolling 50% with ATR (flow), so you don’t lose context when price escapes prior ranges. The cloud tells you who’s in control (fast vs. slow structure). The rolling 50% + ATR tells you how far is “too far” now.
➖➖➖
🧠 What it does (at a glance)
🔸Structural Equilibrium × 2 (Fib1/Fib2)
Two independent 50% midpoints formed from swing pivots (configurable Left/Right bars + optional smoothing). Their gap is the Midpoint Cloud = structural “fair value” zone.
🔸Rolling 50% + ATR Bands
A rolling highest/lowest window computes an always-current 50% rolling midpoint plot; ±ATR × length envelopes define a soft value area and over-stretch boundaries.
🔸Actionable Visuals
Optional fill between Fib1/Fib2, labels, and candle-overlay modes to instantly read regime (above both / below both / between).
🔸Smart Defaults
Timeframe-aware presets for L/R pivots & smoothing; full manual overrides available.
➖➖➖
⚙️ Calculations (plain-English)
🔸Pivot midpoints (Fib1 & Fib2):
1) Detect a swing using `Left/Right` bars
2) Take the swing’s high/low → compute 50%
3) (Optional) Smooth the line (SMA) to stabilize on noisy TFs
4) Repeat with a different sensitivity to get two distinct midpoints
🔸Rolling midpoint:
Highest High / Lowest Low over the last *N* bars → (HH + LL) / 2
🔸ATR levels:
`Upper = Rolling50 + ATR × Mult`, `Lower = Rolling50 − ATR × Mult`
(Typical: ATR length 14–21; Multipliers 2.236 for L1, 5.382 for L2)
➖➖➖
🤖 Auto-Configured Presets (with Manual Override)
💡Goal: make the midpoints “just work” on common timeframes while still letting you dial them in.
💡How Auto Presets work
When Auto Presets = ON, the script picks sensible L/R/S (Left bars / Right bars / Smoothing) for Fib Trend 1 and Fib Trend 2 based on chart timeframe.
🔸Fib 1 (fast) emphasizes *micro-structure* for quicker bias shifts.
🔸Fib 2 (slow) emphasizes *macro-structure* for anchor/bias context.
These defaults keep Fib 1 responsive without jitter and Fib 2 stable without lag.
➡️ Turn Auto Presets = OFF to take full control with the manual inputs described below.
➖➖➖
🛠 Manual Fib Midpoint Settings (when Auto = OFF)
💡Each midpoint uses three knobs:
🔸Pivot Left (L): bars to the left that must be lower/higher to qualify a swing
🔸Pivot Right (R): bars to the right that must be lower/higher to confirm the swing
🔸Smoothing (S): SMA period applied to the raw 50% midpoint (stabilizes noise)
5-Minute optimized defaults
🔸Fib Trend 1: `L21 / R5 / S55` → responsive local structure (entries/exits, re-balancing zones)
🔸Fib Trend 2: `L55 / R13 / S89` → broader structure (trend context, anchors/stops)
Timeframe guidance
🔸1m–3m: may feel a touch laggy → consider ~`L13 / R3 / S34`
🔸15m–1h: defaults remain strong → optionally ~`L34 / R8 / S89`
🔸4h+ : increase span for stability → `L89–144 / R13–21 / S144–233`
➡️ Rule of thumb: shorter L/R = faster detection, longer S = smoother line. Tune until Fib 1 captures the “active swing” and Fib 2 captures the “dominant swing” without whipsaw.
➖➖➖
🎛 Inputs (quick reference)
🔸Fib Trend 1/2: Source (High/Low/Close), Left/Right bars, Smoothing length, Show/Hide, Cloud fill toggle
🔸Rolling 50%: Lookback length, Price basis (Wicks/Close/HLC3/OHLC4), Plot scope (Full / Last N / None)
🔸ATR Bands: ATR length, Multipliers (L1/L2), Plot scope, Line width/colors
🔸Overlay & Labels: Candle overlay mode, Label padding/size, 50% centerline toggle, Plot widths
➖➖➖
🖍️ Candle Coloring & Overlay Modes
💡Purpose: make trend instantly visible on the candles and ATR levels.
1) Color Logic (dropdown)
🔸 Fib Midpoints — Colors by position of price vs. Fib 1 & Fib 2
🔸ATR Zones — Colors by which ATR zone price is in relative to the Rolling 50%
➡️ Price Reference: Choose the input used for the decision (Close, HL2, OHLC3, OHLC4).
➡️Tip: Close is crisp; HL2/OHLC variants are smoother.
2) Overlay Style (dropdown)
🔸 None — No visual change to candles
🔸 Bar Color — Uses `barcolor()` to tint built-in candles (this takes into account your Trading View settings, for instance if you have wicks set to white, they will show up as white with this setting)
🔸 PlotCandles — Draws unified custom candles (body, wick, border) with the same color for maximum clarity
💡Practical use
🔸 Pick Fib Midpoints to read structural bias at a glance (above/below/between the cloud).
🔸 Pick ATR Zones to read value vs. stretch around the Rolling 50% (mean-reversion vs. trend extension).
➖➖➖
📘 How to use
A) Trend confirmation
- Strong bullish bias when price holds above both structural mids; strong bearish when below both.
- Use the Rolling 50% + ATR as a dynamic re-entry zone: pullbacks that respect ATR(L1) often continue the prevailing trend.
B) Transition / mean reversion
- Inside the Cloud (between Fib1 & Fib2) treat behavior as neutralization/re-balancing; range tactics tend to outperform momentum plays.
- In ranges, fades near ±ATR around the rolling 50% can mark short-term edges.
C) Breakout context
- When price leaves the Cloud, the Rolling 50% keeps you anchored so price never feels “floating.” A clean hold outside ATR(L1/L2) suggests regime strength; quick re-entries hint at traps.
➖➖➖
🖼 Chart examples
➡️ Each snapshot shows how the Cloud (structure) and the Rolling 50% + ATR (flow) work together.
1) 1-Minute Downtrend – Cloud as Dynamic Ceiling
- The Cloud slopes down; pullbacks repeatedly fail under the Cloud’s underside.
- Rolling 50% (dashed mid) + ATR(L1) act as a reversion band: rallies stall near upper ATR and rotate lower.
2) 15-Minute Persistent Drift – Structure Guides, Flow Times Entries
- Long drift lower with Cloud overhead.
- Consolidations near the rolling mid resolve in the trend direction; ATR bands frame risk on each attempt.
3) 15-Minute Uptrend (BTC) – From Cloud Escape to Value Stair-Step
- After escaping the prior Cloud, rolling 50% + ATR establish a new higher value area.
- Pullbacks into ATR(L1) produce orderly stair-steps; Cloud remains supportive on deeper dips
4) 5-Minute BTC – Pullback to Value then Rotate
- Strong leg up; retrace tags lower ATR band and rotates back toward the rolling mid.
- Labels (Fib1/Fib2) make the structural context explicit for decision-making.
➖➖➖
🧪 Starter presets
- Intraday (5–15m): Fib1 ~ L21/R5 (smooth 5), Fib2 ~ L55/R13 (smooth 9) • Rolling = 55 • ATR = 14 • L1 = 2.5x, L2 = 5.0x
- Scalping: Shorten lookbacks & smoothing; keep ATR multipliers similar, or tighten L1.
- Swing: Lengthen all lookbacks; consider ATR length 21–28.
➖➖➖
🏁Final Word
This script is not just a visual tool, it’s a complete trend and structure framework. Whether you're looking for clean trend alignment, dynamic support/resistance, or early warning signs of a reversal, this system is tuned to help you react with confidence — not hindsight.
Rembember, no single indicator should be used in isolation. For best results, combine it with price action analysis, higher-timeframe context, and complementary tools like trendlines, moving averages etc Use it as part of a well-rounded trading approach to confirm setups — not to define them alone.
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💡Turn logic into clarity. Structure into trades. And uncertainty into confidence.
Sessions [Trade Tribe HQ]Color-coded session ranges with ADR% labels to help you trade smarter, not harder.
This tool marks New York, London, Tokyo, and Sydney sessions, showing their ranges, highs/lows, VWAPs, and ADR%.
🔹 Key Features
Colored session boxes (NY, London, Tokyo, Sydney)
Session highs & lows, VWAP, and trendlines
Dashboard showing active sessions, volume, and %ADR
ADR% labels at session close
🔹 How It Helps
Spot session traps, moves, and reversals faster
Manage expectations using ADR% (no chasing over-extended moves)
Identify overlap zones (London → NY) for volatility spikes
Simplify cycle tracking across global markets
Market Sessions Marker—making it easy to see where the energy has been spent and where opportunity is building next.
Created with ❤️ by TraderChick – part of the Trade Tribe HQ community.
If you found this tool useful, check out my profile for more strategies, classes, and resources.
Adaptive HMA SignalsAdaptive HMA Signals
This indicator pairs nicely with the Contrarian 100 MA and can be located here:
Overview
The "Adaptive HMA Signals" indicator is a sophisticated technical analysis tool designed for traders aiming to capture trend changes with precision. By leveraging Hull Moving Averages (HMAs) that adapt dynamically to market conditions (volatility or volume), this indicator generates actionable buy and sell signals based on price interactions with adaptive HMAs and slope analysis. Optimized for daily charts, it is highly customizable and suitable for trading forex, stocks, cryptocurrencies, or other assets. The indicator is ideal for swing traders and trend followers seeking to time entries and exits effectively.
How It Works
The indicator uses two adaptive HMAs—a primary HMA and a minor HMA—whose periods adjust dynamically based on user-selected market conditions (volatility via ATR or volume via RSI). It calculates the slope of the primary HMA to identify trend strength and generates exit signals when the price crosses the minor HMA under specific slope conditions. Signals are plotted as circles above or below the price, with inverted colors (white for buy, blue for sell) to enhance visibility on any chart background.
Key Components
Adaptive HMAs: Two HMAs (primary and minor) with dynamic periods that adjust based on volatility (ATR-based) or volume (RSI-based) conditions. Periods range between user-defined minimum and maximum values, adapting by a fixed percentage (3.141%).
Slope Analysis: Calculates the slope of the primary HMA over a 34-bar period to gauge trend direction and strength, normalized using market range data.
Signal Logic: Generates buy signals (white circles) when the price falls below the minor HMA with a flat or declining slope (indicating a potential trend reversal) and sell signals (blue circles) when the price rises above the minor HMA with a flat or rising slope.
Signal Visualization: Plots signals at an offset based on ATR for clarity, using semi-transparent colors to avoid chart clutter.
Mathematical Concepts
Dynamic Period Adjustment:
Primary HMA period adjusts between minLength (default: 144) and maxLength (default: 200).
Minor HMA period adjusts between minorMin (default: 55) and minorMax (default: 89).
Periods decrease by 3.141% under high volatility/volume and increase otherwise.
HMA Calculation:
Uses the Hull Moving Average formula: WMA(2 * WMA(src, length/2) - WMA(src, length), sqrt(length)).
Provides a smoother, faster-responding moving average compared to traditional MAs.
Slope Calculation:
Computes the slope of the primary HMA using a 34-bar period, normalized by the market range (highest high - lowest low over 34 bars).
Slope angle is converted to degrees using arccosine for intuitive trend strength interpretation.
Signal Conditions:
Buy: Slope ≥ 17° (flat or rising), price < minor HMA, low volatility/volume.
Sell: Slope ≤ -17° (flat or declining), price > minor HMA, low volatility/volume.
Signals are triggered only on confirmed bars to avoid repainting.
Entry and Exit Rules
Buy Signal (White Circle): Triggered when the price crosses below the minor HMA, the slope of the primary HMA is flat or rising (≥17°), and volatility/volume is low. The signal appears as a white circle above the price bar, offset by 0.72 * ATR(5).
Sell Signal (Blue Circle): Triggered when the price crosses above the minor HMA, the slope of the primary HMA is flat or declining (≤-17°), and volatility/volume is low. The signal appears as a blue circle below the price bar, offset by 0.72 * ATR(5).
Exit Rules: Exit a buy position on a sell signal and vice versa. Combine with other tools (e.g., support/resistance, RSI) for additional confirmation. Always apply proper risk management.
Recommended Usage
The "Adaptive HMA Signals" indicator is optimized for daily charts but can be adapted to other timeframes (e.g., 1H, 4H) with adjustments to period lengths. It performs best in trending or range-bound markets with clear reversal points. Traders should:
Backtest the indicator on their chosen asset and timeframe to validate signal reliability.
Combine with other technical tools (e.g., trendlines, Fibonacci retracements) for stronger trade setups.
Adjust minLength, maxLength, minorMin, and minorMax based on market volatility and timeframe.
Use the Charger input to toggle between volatility (ATR) and volume (RSI) adaptation for optimal performance in specific market conditions.
Customization Options
Source: Choose the price source (default: close).
Show Signals: Toggle visibility of buy/sell signals (default: true).
Charger: Select adaptation trigger—Volatility (ATR-based) or Volume (RSI-based) (default: Volatility).
Main HMA Periods: Set minimum (default: 144) and maximum (default: 200) periods for the primary HMA.
Minor HMA Periods: Set minimum (default: 55) and maximum (default: 89) periods for the minor HMA.
Slope Period: Fixed at 34 bars for slope calculation, adjustable via code if needed.
Why Use This Indicator?
The "Adaptive HMA Signals" indicator combines the responsiveness of HMAs with dynamic adaptation to market conditions, offering a robust tool for identifying trend reversals. Its clear visual signals, customizable periods, and adaptive logic make it versatile for various markets and trading styles. Whether you’re a beginner or an experienced trader, this indicator enhances your ability to time entries and exits with precision.
Tips for Users
Test the indicator thoroughly on your chosen market and timeframe to optimize settings (e.g., adjust period lengths for non-daily charts).
Use in conjunction with price action or other indicators (e.g., RSI, MACD) for stronger trade confirmation.
Monitor volatility/volume conditions to ensure the Charger setting aligns with market dynamics.
Ensure your chart timeframe aligns with the selected period lengths for accurate signal generation.
Apply strict risk management to protect against false signals in choppy markets.
Happy trading with the Adaptive HMA Signals indicator! Share your feedback and strategies in the TradingView community!
Effort vs Result TRFxThe Effort vs Result (EVR) indicator is designed to identify high-probability reversal signals based on volume and price action dynamics. It highlights points where the market “effort” (high volume) does not correspond to an immediate “result” (price continuation), providing actionable trade setups for both bullish and bearish scenarios.
Features:
Detects bullish EVR signals when a previous high-volume sell candle is followed by a strong bullish candle that sweeps the previous low.
Detects bearish EVR signals when a previous high-volume buy candle is followed by a strong bearish candle that sweeps the previous high.
Sticky arrows plot automatically above or below the candle, ensuring the signal moves with the price bar.
Considers inside bars, wick size, and relative volume to filter low-quality setups.
Fully compatible with multiple timeframes.
Inputs:
Volume Multiplier: Sets how much higher the current candle’s volume should be compared to the previous candle to count as high volume.
Min Wick % of Candle: Minimum wick size relative to the candle body to filter insignificant bars.
Max Inside Bars to Ignore: Number of inside bars between the previous candle and the EVR candle to ignore minor consolidations.
Usage:
(Green Arrow): Enter long when a green arrow appears below the candle. Place stop-loss slightly below the previous swing low.
(Red Arrow): Enter short when a red arrow appears above the candle. Place stop-loss slightly above the previous swing high.
Can be combined with support/resistance levels, trendlines, or other technical indicators for higher accuracy.
Benefits:
Simple and clean visual signals with tiny arrows that move with candles.
Helps traders identify high-probability reversal points based on volume and price action.
Ideal for intraday and swing trading strategies.
Contrarian Period High & LowContrarian Period High & Low
This indicator pairs nicely with the Contrarian 100 MA and can be located here:
Overview
The "Contrarian Period High & Low" indicator is a powerful technical analysis tool designed for traders seeking to identify key support and resistance levels and capitalize on contrarian trading opportunities. By tracking the highest highs and lowest lows over user-defined periods (Daily, Weekly, or Monthly), this indicator plots historical levels and generates buy and sell signals when price breaks these levels in a contrarian manner. A unique blue dot counter and action table enhance decision-making, making it ideal for swing traders, trend followers, and those trading forex, stocks, or cryptocurrencies. Optimized for daily charts, it can be adapted to other timeframes with proper testing.
How It Works
The indicator identifies the highest high and lowest low within a specified period (e.g., daily, weekly, or monthly) and draws horizontal lines for the previous period’s extremes on the chart. These levels act as dynamic support and resistance zones. Contrarian signals are generated when the price crosses below the previous period’s low (buy signal) or above the previous period’s high (sell signal), indicating potential reversals. A blue dot counter tracks consecutive buy signals, and a table displays the count and recommended action, helping traders decide whether to hold or flip positions.
Key Components
Period High/Low Levels: Tracks the highest high and lowest low for each period, plotting red lines for highs and green lines for lows from the bar where they occurred, extending for a user-defined length (default: 200 bars).
Contrarian Signals: Generates buy signals (blue circles) when price crosses below the previous period’s low and sell signals (white circles) when price crosses above the previous period’s high, designed to capture potential reversals.
Blue Dot Tracker: Counts consecutive buy signals (“blue dots”). If three or more occur, it suggests a stronger trend, with the table recommending whether to “Hold Investment” or “Flip Investment.”
Action Table: A 2x2 table in the bottom-right corner displays the blue dot count and action (“Hold Investment” if count ≥ 4, else “Flip Investment”) for quick reference.
Mathematical Concepts
Period Detection: Uses an approximate bar count to define periods (1 bar for Daily, 5 bars for Weekly, 20 bars for Monthly on a daily chart). When a new period starts, the previous period’s high/low is finalized and plotted.
High/Low Tracking:
Highest high (periodHigh) and lowest low (periodLow) are updated within the period.
Lines are drawn at these levels when the period ends, starting from the bar where the extreme occurred (periodHighBar, periodLowBar).
Signal Logic:
Buy signal: ta.crossunder(close , prevPeriodLow) and not lowBroken and barstate.isconfirmed
Sell signal: ta.crossover(close , prevPeriodHigh) and not highBroken and barstate.isconfirmed
Flags (highBroken, lowBroken) prevent multiple signals for the same level within a period.
Blue Dot Counter: Increments on each buy signal, resets on a sell signal or if price exceeds the entry price after three or more buy signals.
Entry and Exit Rules
Buy Signal (Blue Circle): Triggered when the price crosses below the previous period’s low, suggesting a potential oversold condition and buying opportunity. The signal appears as a blue circle below the price bar.
Sell Signal (White Circle): Triggered when the price crosses above the previous period’s high, indicating a potential overbought condition and selling opportunity. The signal appears as a white circle above the price bar.
Blue Dot Tracker:
Increments blueDotCount on each buy signal and sets an entryPrice on the first buy.
Resets on a sell signal or if price exceeds entryPrice after three or more buy signals.
If blueDotCount >= 3, the table suggests holding; if >= 4, it reinforces “Hold Investment.”
Exit Rules: Exit a buy position on a sell signal or when price exceeds the entry price after three or more buy signals. Combine with other tools (e.g., trendlines, support/resistance) for additional confirmation. Always apply proper risk management.
Recommended Usage
The "Contrarian Period High & Low" indicator is optimized for daily charts but can be adapted to other timeframes (e.g., 1H, 4H) with adjustments to the period bar count. It excels in markets with clear support/resistance levels and potential reversal zones. Traders should:
Backtest the indicator on their chosen asset and timeframe to validate signal reliability.
Combine with other technical tools (e.g., moving averages, Fibonacci levels) for stronger trade confirmation.
Adjust barsPerPeriod (e.g., ~120 bars for Weekly on hourly charts) based on the chart timeframe and market volatility.
Monitor the action table to guide position management based on blue dot counts.
Customization Options
Period Type: Choose between Daily, Weekly, or Monthly periods (default: Monthly).
Line Length: Set the length of high/low lines in bars (default: 200).
Show Highs/Lows: Toggle visibility of period high (red) and low (green) lines.
Max Lines to Keep: Limit the number of historical lines displayed (default: 10).
Hide Signals: Toggle buy/sell signal visibility for a cleaner chart.
Table Display: A fixed table in the bottom-right corner shows the blue dot count and action, with yellow (Hold) or green (Flip) backgrounds based on the count.
Why Use This Indicator?
The "Contrarian Period High & Low" indicator offers a unique blend of support/resistance visualization and contrarian signal generation, making it a versatile tool for identifying potential reversals. Its clear visual cues (lines and signals), blue dot tracker, and actionable table provide traders with an intuitive way to monitor market structure and manage trades. Whether you’re a beginner or an experienced trader, this indicator enhances your ability to spot key levels and time entries/exits effectively.
Tips for Users
Test the indicator thoroughly on your chosen market and timeframe to optimize settings (e.g., adjust barsPerPeriod for non-daily charts).
Use in conjunction with price action or other indicators for stronger trade setups.
Monitor the action table to decide whether to hold or flip positions based on blue dot counts.
Ensure your chart timeframe aligns with the selected period type (e.g., daily chart for Monthly periods).
Apply strict risk management to protect against false breakouts.
Happy trading with the Contrarian Period High & Low indicator! Share your feedback and strategies in the TradingView community!
CCI vs Two EMAs + Trendlines + Breakout HighlightPerfect indicator which analyzes the cci4000 & 2 EMAS.
Option Trend for Nifty & Bank Nifty (Indian Market)This is an advanced multi-system trading indicator for TradingView, offering a comprehensive suite of tools for technical analysis and trading decision support .
Main Features
Trendline Detection: Identifies bullish and bearish trendlines automatically using swing highs and lows, with optional labeling of key price structure (Higher Highs, Lower Lows, etc.) and customizable line colors and styles.
Signal & Trend Systems: Includes both a crossover signal system (for buy/sell entries) and a multi-period trend-following system, which uses enhanced moving averages and dynamic trailing levels to adapt to different market conditions.
Supply & Demand Zones: Automatically detects and marks potential supply and demand zones based on pivot structures and ATR buffers, helping spot logical areas for price reaction or reversal.
Support & Resistance: Plots periodic support/resistance and macro (long-term) levels, with user-defined periods and the ability to visualize volume delta for each zone.
Theil-Sen Estimator: Optionally adds a statistical regression channel using the robust Theil-Sen method to identify trend direction and breaks for long-term analysis.
RSI/KDE Analysis: Implements relative strength index (RSI) analysis with kernel density estimation (KDE) to detect pivot points with probability labeling and color-coded signals for high-confidence reversals.
Dashboards & Alerts: Provides multitimeframe dashboards summarizing trend, EMA signals, and momentum across up to five timeframes, plus integrated alerting for all major events (entries, exits, zone breaks, etc.).
Customization & Usability
Extensive input settings for periods, color themes, line widths, and label visibility.
Can display visual cloud bands, trend ribbons, and supply/demand boxes as overlays on price charts for enhanced clarity.
Open-source and for educational use under permissive licensing, not affiliated with TradingView.
This indicator is designed to deliver a full-featured market map, combining price action, trend, support/resistance, and probabilistic signals for discretionary or semi-automated trading.
