Momentum Candle By SkyroothMomentum Candle By Skyrooth highlights expansion candles — the bars where one
side takes control decisively — and filters out the ordinary bars that only look
big because volatility happened to be high at the time.
WHAT PROBLEM THIS SOLVES
Most price action methods depend on a single instruction: "wait for
displacement". A break of structure only counts if the candle that caused it was
decisive. An order block only counts if the move leaving it was strong.
The problem is that "strong" is usually judged by eye, and the eye is unreliable.
A 40 point candle is large on a quiet morning and unremarkable during a news
release. Traders end up calling the same candle valid or invalid depending on
what they want to see.
This indicator applies one fixed measurement instead.
HOW IT WORKS
A candle is marked when all of the following are true:
1. BODY DOMINANCE — the body is large relative to the total range of the bar, so
the close finishes near the extreme rather than in the middle. This is what
separates a decisive bar from a bar that spent the session being rejected.
2. RANGE VS RECENT VOLATILITY — the range is compared against a rolling average
of recent ranges, not against a fixed point value. This is what makes the
measurement adapt: the same threshold works on a quiet session and a volatile
one, and on gold as well as an index.
3. VOLUME CONFIRMATION — the bar is compared against its own recent volume
average. Expansion on thin volume is usually a liquidity gap rather than
participation.
4. DIRECTIONAL AGREEMENT — the bar's direction is checked against the prevailing
trend, so continuation bars are separated from isolated spikes.
Bars meeting the conditions are coloured and marked on the chart. Everything
else is left alone.
HOW TO USE IT
This is a filter, not an entry signal. It answers one question — "was that move
decisive?" — and nothing else. There is no entry, stop or target here.
Typical use:
- CONFIRMING A STRUCTURE BREAK. When price breaks a swing high or low, check
whether the breaking candle is marked. An unmarked break is more likely to be
a liquidity sweep that reverses.
- VALIDATING AN ORDER BLOCK OR IMBALANCE. The candle that leaves the zone should
be marked. If the departure was weak, the zone is weak.
- AVOIDING CHASING. A marked candle means the move already happened. Wait for a
retracement into the area the candle originated from rather than entering at
the extreme.
SETTINGS
- Body ratio threshold — minimum share of the range the body must occupy.
Raise it for fewer, cleaner signals.
- Volatility lookback — number of bars in the rolling range average.
- Volume multiplier — how far above its own average the bar's volume must be.
Set to zero to disable the volume condition on instruments with unreliable
volume data, such as spot forex.
- Trend filter — enable to keep only bars aligned with the prevailing direction.
NOTES AND LIMITATIONS
- Signals are confirmed on bar close. An intrabar candle can meet the conditions
and then lose them before closing.
- Volume conditions depend on the feed. Centralised futures volume is reliable;
spot forex volume is broker specific and often is not.
- A marked candle describes what already happened. It carries no claim about
what happens next, and no win rate is implied.
- Works on any symbol and timeframe, though the volume condition is most
meaningful on instruments with genuine exchange volume. Indikator
SMI Ergodic Oscillator PROSMI Ergodic Oscillator PRO
The SMI Ergodic Oscillator PRO is a momentum indicator designed to help traders identify changes in the strength and direction of price movement.
The indicator displays a histogram, making momentum behavior easy to visualize:
🟢 Green/Lime: momentum is gaining strength or positive slope.
🔴 Red: momentum is weakening or showing negative slope.
Larger bars: indicate stronger momentum.
Smaller bars: may indicate declining momentum and a possible loss of strength.
The main purpose of the indicator is not to generate trades by itself, but to help confirm market direction and identify potential changes in momentum.
How to Use
1. Trend Confirmation
During an uptrend, look for a sequence of consistent positive bars. Sustained momentum can provide additional confirmation that the current move remains strong.
During a downtrend, look for persistent negative bars.
2. Momentum Changes
A change in histogram color can highlight a potential shift in market momentum.
Red → Green
May indicate improving bullish momentum.
Green → Red
May indicate weakening bullish momentum or increasing bearish momentum.
Color changes should be evaluated together with price action, market structure, and the overall trend.
3. Loss of Momentum
When histogram bars begin to decrease in size, even while remaining on the same side, this may indicate that the current movement is losing strength.
This can be used as an alert to:
Reduce exposure
Protect an existing position
Wait for additional confirmation
Monitor for a potential reversal
Parameter Settings
The indicator provides three main parameters:
Parameter Practical Function Effect
Long Length Controls the longer-term sensitivity Higher values = smoother response
Short Length Controls responsiveness to recent price movements Lower values = faster response
Signal Length Controls signal smoothing Higher values = less noise
Suggested Settings
Balanced — 20 / 5 / 5
A good starting configuration for general market analysis and most timeframes.
Fast — 10 / 3 / 3
More responsive to recent momentum changes. Suitable for traders looking for earlier signals, but it may produce more noise.
Conservative — 30 / 7 / 7
Produces a smoother reading and reduces sensitivity to smaller market fluctuations.
Very Conservative — 50 / 10 / 10
Designed for traders who prefer to focus on larger and more sustained market movements.
Choosing the Right Settings
There is no universal "best" configuration. Parameters should be adapted to:
Asset: Crypto, Forex, stocks, indices, etc.
Timeframe: Scalping, day trading, or swing trading.
Volatility: Highly volatile markets may require more conservative settings.
Trading style: Faster settings can be useful for earlier momentum detection, while slower settings can provide stronger confirmation.
Simple Trading Approach
A practical approach is to use the indicator in combination with price structure and market context.
Potential Long Setup:
Favorable market structure + positive momentum + confirmation from the histogram.
Potential Short Setup:
Favorable bearish structure + negative momentum + confirmation from the histogram.
Avoid: entering a trade solely because the histogram changes color. A color change is better treated as a confirmation or warning signal, rather than an independent trading signal.
Important Notice
The SMI Ergodic Oscillator PRO is a technical analysis tool designed to assist with market analysis. It does not guarantee trading results and should not be considered financial advice. Always combine the indicator with proper risk management and independent market analysis. Indikator
Coppock Curve Multi-Filter [MarkitTick]💡 A dual-momentum oscillator built on the classic Coppock Curve, extended with an optional adaptive source pre-filter, an ADX strength gate, and a full ATR-based trade-management layer with staged take-profits, on-chart price levels, and a live dashboard. The core wave is a weighted moving average of two rate-of-change readings, but everything measured downstream of that wave — signal timing, trend bias, and risk levels — can be reshaped by up to eight independent, toggleable filters, giving traders a single oscillator that can behave anywhere from "classic long-term Coppock" to a tightly gated, multi-condition entry engine.
✨ Originality and Utility
The stock Coppock Curve is a single-purpose, long-only momentum tool: sum two rate-of-change readings, smooth with a weighted moving average, and watch for crosses above zero. This script keeps that foundation intact but restructures it into a bidirectional signal engine with a stack of independent confirmation layers that the original concept never included.
The key structural change is the adaptive source stage. Rather than feeding raw closing price directly into the rate-of-change calculations, the script offers a choice of eight different smoothing methods — including a custom Kalman Filter estimator and a custom LLAMA (Linear-Lag Adaptive Moving Average) function — that first condition the price series before Coppock's ROC math is applied. This means the character of the entire curve can be tuned from responsive to heavily smoothed without altering the underlying two-ROC-plus-WMA structure that defines the Coppock method.
Layered on top of that are seven optional gating and confirmation mechanisms (ADX strength, divergence, slope acceleration, volume, higher-timeframe alignment, volatility-adjusted zero line, and signal persistence) that traders can combine in any subset. Because each filter operates independently and can be switched on or off, the same core wave can be configured for a slow trend-confirmation approach or a fast, tightly-filtered signal generator, giving the tool a much broader utility range than a standard Coppock plot.
Beyond signal generation, the script converts each qualifying cross into a full trade plan: an ATR-derived stop-loss, three R-multiple take-profit tiers, live price levels drawn on the chart, and a real-time dashboard summarizing bias, filter states, and trade levels — none of which exist in the original Coppock Curve concept or in standard TradingView implementations of it.
🔬 Methodology and Concepts
● Core Wave Construction
The engine begins with an adaptive source stage. If no adaptive filter is selected, the raw chosen source (default: close) feeds directly into the calculation. If a filter is selected, the source is pre-smoothed using one of the following:
Simple, Exponential, or RMA-based moving averages
A Double WMA (a weighted moving average applied twice in succession, producing extra lag reduction)
A Triple VWMA (three successive volume-weighted moving average passes)
A Hull Moving Average
A custom LLAMA function, which computes a simple moving average over the lookback window, then adds a linear slope term (calculated from the change in price across the window divided by the window length) scaled by half the window length — effectively projecting the average forward along its own recent trajectory
A custom Kalman Filter estimator, which maintains a running estimate and error variance, calculates a Kalman gain each bar from the ratio of predicted error to total error, and blends the new price into the estimate proportionally to that gain — placing more weight on new data when the filter's own uncertainty is high, and more weight on the existing estimate when it is low
Once the (optionally smoothed) source is established, two Rate of Change values are calculated against it — a long lookback and a short lookback, independently configurable. These two ROC values are summed and passed through a weighted moving average, producing the final Coppock Curve value. This is structurally identical to the classic Coppock formula, but with the adaptive pre-filter as an optional intermediate step.
• ADX Strength Filter
When enabled, the script calculates the Directional Movement Index (+DI, -DI, ADX) over a configurable length. A signal — whether a slope change, a cross, or a zero-line cross — is only considered valid if the ADX reading is at or above the user-defined threshold. This filters out Coppock movements that occur during weak or directionless conditions.
• Slope and Cross Detection
The script tracks whether the curve is rising or falling bar-to-bar, and separately detects two types of crosses: a cross of the curve against its own prior value (used as the primary bull/bear signal) and a cross of the curve against the zero line (used as a secondary trend-state signal). Both cross types respect the ADX filter when it is active.
• Signal Locking
A "Lock Signal" input freezes the active signal and trade levels on the most recent bar, preventing new signals from overwriting the currently displayed trade plan — useful for holding a specific setup visible while monitoring live price action.
● Trade-Level Automation
Every new bullish or bearish cross (confirmed and unlocked) triggers a full trade-plan calculation:
Entry is set to the prior bar's close
Stop-loss is placed at a configurable multiple of ATR away from entry, in the direction opposing the trade
Three take-profit levels are calculated as configurable R-multiples of the initial risk distance (the entry-to-stop distance), projected in the trade's favor
Each level's distance from entry is also expressed as a percentage for quick reference
These levels persist on the chart until a new opposing signal fires (or, if Lock Signal is active, until manually released), and are dynamically extended to the current bar so the trade plan remains visible in real time. Take-profit and stop labels update their text once price actually touches each respective level, marking it as hit along with the realized percentage move.
● Optional Confirmation Filters
Seven additional filters exist as inputs in the script but should be understood as configuration flags a trader can layer onto the core signal logic depending on their own methodology:
Divergence Filter — intended to suppress cross signals that run counter to a detected price/Coppock divergence
Slope Acceleration Filter — intended to require the curve's slope itself to be increasing, not merely positive, before validating a signal
Volume Confirmation Filter — intended to require current volume to exceed its moving average before a signal is accepted
HTF Alignment Filter — intended to require a higher-timeframe Coppock reading to agree with the signal's direction
Volatility-Adjusted Zero Line — intended to require zero-line crosses to clear a noise band derived from the indicator's own recent volatility, reducing whipsaw signals near the zero line
Signal Persistence Filter — intended to require the curve's direction to hold for a minimum number of bars before a signal is treated as valid
Traders should treat these as intended-purpose toggles per their input tooltips and confirm behavior against the ADX filter and core cross logic, which are the two filters fully wired into the signal path in this build.
🎨 Visual Guide
● Main Panel (Separate Pane)
The primary line plot shows the Coppock Curve itself. It is colored using the Bull Color when the curve is rising and the ADX filter (if active) passes, the Bear Color when falling under the same condition, and the Neutral Color otherwise.
A histogram of the same Coppock value is plotted in columns beneath the line, using a four-tier color scheme: strong bull shading when the curve is above zero and rising, weak bull shading when above zero but not rising, weak bear shading when below zero but rising, and strong bear shading when below zero and falling.
A dashed horizontal zero line marks the neutral threshold that separates bullish and bearish curve territory.
Small triangle markers appear directly on the curve at the exact bar where it crosses zero — an upward triangle in Bull Color for an upward zero-cross, and a downward triangle in Bear Color for a downward zero-cross.
● Price Chart Overlay
When candle coloring is enabled, the price candles themselves are recolored using the same four-tier histogram coloring described above, turning the price chart into a visual heatmap of underlying Coppock strength and direction.
When a new signal fires and trade levels are enabled, five horizontal lines are drawn directly on price: a solid stop-loss line, a dashed entry line, and three dashed take-profit lines with progressively increasing opacity from TP1 to TP3. Each line carries a right-aligned label showing its role and exact price.
A shaded "risk zone" fills the area between the stop-loss and entry lines, and a "reward zone" fills the area between the entry and TP3 lines, giving an immediate visual sense of the risk-to-reward geometry of the active trade plan.
Once a take-profit or stop level is touched by price, its label updates in place to show a hit confirmation along with the realized percentage gain or loss.
● Dashboard Table
A compact table (position configurable) displays, in real time: the current symbol and timeframe, the Lock Signal state, the raw Coppock value, the current bias (Bullish / Bearish / Neutral, color-coded), the individual long and short ROC readings, whether the curve is currently above or below zero, and — when trade levels are enabled — the live Entry, SL, TP1, TP2, and TP3 prices. If the ADX filter is active, its current reading is shown alongside a pass/fail color cue. If an adaptive filter is selected, its name is displayed for quick reference.
📖 How to Use
Treat a bullish cross (curve turning up) as a potential long-side signal, and a bearish cross (curve turning down) as a potential short-side signal, especially when it aligns with a zero-line cross in the same direction.
Use the zero line as a broader trend-state filter: readings above zero generally reflect positive intermediate-term momentum, while readings below zero reflect negative momentum, independent of the immediate slope.
Enable the ADX filter to restrict signals to periods of measurable trend strength, reducing signals generated during flat or choppy conditions.
Select an adaptive filter method to change the responsiveness of the underlying source feeding the Coppock calculation — faster methods like EMA or the Kalman Filter increase sensitivity, while methods like the Triple VWMA or SMA produce a smoother, slower curve.
When a signal fires, use the automatically plotted Entry, SL, and TP1–TP3 lines as a starting reference for trade structure, and adjust position sizing according to the displayed stop distance and your own risk tolerances.
Use candle heatmap coloring as a quick visual scan across the chart to spot where momentum has historically been strongest or weakest, independent of reading the oscillator pane directly.
Configure the webhook alert action strings in the Alerts group to match the payload keys expected by your automation or webhook receiver before relying on the JSON-formatted alerts for execution.
⚙️ Inputs and Settings
• Core Settings
Source — the price series the calculation is based on (default: close)
Long ROC Length — lookback for the long-term rate-of-change component
Short ROC Length — lookback for the short-term rate-of-change component
WMA Smoothing Length — window for the final weighted moving average applied to the combined ROC values
• Filters
Use ADX Filter / ADX Threshold / ADX Length — enables trend-strength gating and configures its sensitivity
Adaptive Filter / Adaptive Filter Length — selects the pre-smoothing method applied to price before the ROC/WMA math, and its lookback window
Use Divergence Filter / Divergence Pivot Lookback — configuration for suppressing signals against detected divergence
Use Slope Acceleration Filter — configuration for requiring accelerating slope before a signal
Use Volume Confirmation Filter / Volume MA Length — configuration for requiring above-average volume
Use HTF Alignment Filter / HTF Alignment Timeframe — configuration for requiring higher-timeframe agreement
Use Volatility-Adjusted Zero Line / Volatility Zero Band Multiple / Volatility Zero Band Length — configuration for a noise-adjusted zero-cross threshold
Use Signal Persistence Filter / Persistence Bars — configuration for requiring a minimum number of bars of consistent direction
• Trade Tools
Lock Signal — freezes the currently active signal and trade levels
SL ATR Multiple — sets stop-loss distance as a multiple of ATR
TP1 / TP2 / TP3 R-Multiple — sets each take-profit distance as a multiple of the initial risk
ATR Length — lookback for the Average True Range calculation used in stop placement
Show Trade Levels — toggles the on-chart lines, labels, and dashboard trade-level rows
• Visuals
Use Candle Coloring — toggles heatmap-style recoloring of price candles
Show Histogram — toggles the columned histogram beneath the main curve
Show Zero-Cross Markers — toggles the triangle markers at zero-line crosses
• Dashboard
Show Dashboard — toggles the on-chart summary table
Position — sets the table's screen position
• Alerts
Action strings for Bull Cross, Bear Cross, Zero Cross Up/Down, Close Long/Short, and TP1/TP2/TP3/SL Hit — these populate the "action" field of each JSON alert payload, allowing the alerts to be mapped directly to webhook or automation logic
• Colors
Full palette control over bull/bear/neutral coloring, histogram tiers, dashboard styling, and all trade-level line and fill colors
🔍 Deconstruction of the Underlying Scientific and Academic Framework
● Rate of Change and the Coppock Curve
The foundation of this script is Edwin Coppock's original curve, published in Barron's in 1962, which sums a long-term and a short-term Rate of Change and smooths the result with a weighted moving average. Rate of Change itself is a first-order momentum measure — the percentage difference between the current value and its value N bars ago — rooted in the broader technical-analysis principle that the velocity of price change often leads price direction itself. Coppock's original design used a WMA specifically because it weights recent data more heavily than a simple average while remaining less reactive to single-bar noise than an exponential average.
● Weighted and Hull Moving Averages
The Weighted Moving Average used both in the final smoothing stage and optionally in the adaptive pre-filter assigns linearly decreasing weights to older data points, a technique long used to balance responsiveness against noise rejection. The Hull Moving Average, developed by Alan Hull, extends this idea by combining WMAs of different lengths in a way designed to reduce lag while preserving smoothness — a documented refinement of the general weighted-average family.
● Kalman Filtering
The Kalman Filter, originally developed by Rudolf Kálmán in the context of control and estimation theory, is a recursive algorithm for estimating an unknown value from a series of noisy observations. In this implementation, the filter maintains a running estimate and an error term, computes a Kalman gain from the ratio of predicted error to total error each bar, and updates the estimate by blending new price data in proportion to that gain. This gives the estimate more responsiveness when its own uncertainty is high and more smoothness when uncertainty is low — the same estimation principle underlying Kalman's original work, applied here to a single noisy input series rather than a multi-variable state system.
● Directional Movement and Trend Strength (Wilder)
The optional ADX filter is built on J. Welles Wilder's Directional Movement System, which derives +DI and -DI from directional price movement smoothed with Wilder's own moving average technique, then compresses their divergence into the Average Directional Index (ADX) as a bounded measure of trend strength independent of direction. Using ADX as a gating condition reflects the broader academic distinction between trend-following and mean-reverting market regimes — Wilder's system was explicitly designed to help separate the two.
● Average True Range and Volatility-Based Risk Sizing
Stop-loss and take-profit distances in this script are derived from Average True Range, also introduced by Wilder, which measures volatility by accounting for gaps as well as intraperiod range. Sizing risk as a multiple of ATR — rather than a fixed point or percentage value — is a widely documented approach in position-sizing literature because it scales stop distance to the instrument's actual recent volatility rather than an arbitrary constant.
● R-Multiples and Risk-Reward Structuring
The three-tiered take-profit structure expresses reward as a multiple of initial risk (an "R-multiple"), a framework popularized in trading risk-management literature to normalize outcomes across trades of different sizes and volatility regimes, allowing performance to be evaluated in terms of risk-adjusted return rather than raw price movement.
⚠️ Disclaimer
All provided scripts and indicators are strictly for educational exploration and must not be interpreted as financial advice or a recommendation to execute trades. We expressly disclaim all liability for any financial losses or damages that may result, directly or indirectly, from the reliance on or application of these tools. Market participation carries inherent risk where past performance never guarantees future returns, leaving all investment decisions and due diligence solely at your own discretion. Indikator
Volatility Regime Engine [TRADION]Volatility Regime Engine is a multi-layer market regime analysis framework designed to identify changes in volatility structure, expansion/compression cycles, directional pressure, and continuation quality.
Rather than treating volatility as a single measurement, the engine evaluates multiple dimensions of market behavior to determine whether price is transitioning into compression, expansion, continuation, exhaustion, or a potentially unstable regime.
The objective is not simply to detect high or low volatility, but to identify how volatility is evolving, whether directional participation supports the move, and whether the current regime has sufficient quality to persist.
CORE ARCHITECTURE
The engine combines several analytical components into a unified regime model:
Volatility Regime
Evaluates the current volatility environment and classifies market conditions according to contraction and expansion behavior.
Fast & Confirmed Scores
Two-stage scoring separates early regime detection from confirmed conditions.
The Fast Score reacts more quickly to developing volatility changes, while the Confirmed Score provides a more stable assessment of established conditions.
This architecture is designed to balance responsiveness with confirmation.
ATR Regime
Measures volatility behavior relative to the instrument's recent range structure, helping distinguish subdued conditions from elevated or extreme volatility environments.
Bandwidth Analysis
Tracks contraction and expansion in the underlying price distribution to identify volatility compression and developing expansion phases.
Relative Volume (RVOL)
Provides participation context by comparing current activity with its historical baseline.
Directional & Setup Bias
Evaluates whether the developing volatility structure favors bullish or bearish conditions.
Bull and Bear Setup Scores quantify the relative strength of each side, while Dominance summarizes the resulting directional imbalance.
Cycle Engine
The Cycle Bias and Cycle State components classify the current phase of the volatility cycle.
Possible conditions include developing ignition, expansion, continuation and exhaustion phases.
This allows the indicator to distinguish between a market that is merely volatile and one that may be entering a structured directional expansion.
Ignition Detection
Ignition logic searches for early evidence that volatility is beginning to transition from a dormant or compressed state into directional expansion.
Bull Ignition and Bear Ignition events are designed as regime-transition signals, not standalone trade entries.
Release Quality
When volatility begins to release, the engine evaluates the quality of that transition.
Release Quality, Quality Grade and Follow Through help determine whether an expansion is developing sufficient structural confirmation or losing momentum.
Macro Continuation
Continuation logic reduces repetitive signaling once a directional regime has already been established.
This allows the engine to distinguish between:
initial ignition,
confirmed release,
established continuation,
and potential exhaustion.
Higher-Timeframe Context
Higher-timeframe regime information is incorporated into the scoring architecture to determine whether the active regime is supported or opposed by broader volatility conditions.
The HTF Quality Modifier adjusts regime quality according to this alignment.
False Expansion Risk
Not every volatility expansion develops into a sustainable move.
The False Expansion Risk model evaluates contextual conditions that may indicate a weak or unstable expansion and classifies the risk accordingly.
This component is intended to provide an additional layer of caution when volatility increases without sufficient structural support.
VISUAL ENGINE
The lower oscillator provides a compact visualization of regime behavior.
Histogram structure represents changes in volatility state and regime intensity, while the accompanying momentum structure helps visualize directional pressure and developing transitions.
Background regime zones provide additional context for compression, expansion and directional phases.
Event markers highlight significant transitions such as:
BULL IGNITION
Potential bullish volatility ignition.
BEAR IGNITION
Potential bearish volatility ignition.
BULL RELEASE
Bullish expansion gaining confirmation.
BEAR RELEASE
Bearish expansion gaining confirmation.
EXHAUST
Potential exhaustion of an extended volatility phase.
Continuation states are intentionally filtered to reduce unnecessary signal repetition.
DASHBOARD
The integrated dashboard provides a real-time summary of the engine, including:
Regime
Fast Score
Confirmed Score
ATR Regime
Bandwidth State
RVOL
Direction
Setup Bias
Bull / Bear Setup
Dominance
Breakout Memory
Cycle Bias
Cycle State
Ignition Score
Macro Continuation
Release Quality
Quality Grade
Follow Through
HTF Regime
HTF Quality Modifier
Risk Adjustment
False Expansion Risk
Active Event
The dashboard is designed to provide a compact overview of the current volatility environment without requiring interpretation of every individual component.
HOW TO USE
Volatility Regime Engine is designed primarily as a market-context and regime-analysis tool.
It can be used to:
identify volatility compression before potential expansion,
detect early bullish or bearish ignition,
evaluate the quality of developing volatility releases,
distinguish expansion from established continuation,
identify potential exhaustion conditions,
compare directional setup strength,
evaluate higher-timeframe regime alignment,
and assess the risk of unstable or false expansion.
The indicator should not be interpreted as a mechanical buy/sell system. Signals represent changes in volatility structure and should be evaluated together with price action, market structure, trend context, support/resistance and appropriate risk management.
NON-REPAINTING DESIGN
The engine is designed around confirmed-bar calculations for signal generation. Historical signals are not intentionally repositioned after confirmation.
Higher-timeframe information is handled with confirmation-oriented logic to minimize look-ahead bias.
IMPORTANT
Volatility expansion does not necessarily imply bullish price movement. Expansion can occur in either direction.
The primary purpose of the engine is to determine when the volatility environment is changing, which side currently has structural dominance, and whether that transition has sufficient quality to develop into continuation.
Volatility Regime Engine is intended for technical analysis, research and educational purposes only. It does not constitute financial or investment advice. Indikator
Wave-Ocean Trend Wave-Ocean Trend
Description
Wave-Ocean Trend is a momentum indicator based on a combination of Exponential Moving Averages (EMA), mean deviation, and Simple Moving Average (SMA).
The indicator is designed to help visualize market direction and momentum changes through the relationship between two waves:
* X1 — Aqua: the fast wave, designed to respond to changes in momentum.
* X2 — Orange: the smoothed wave, used as a reference for identifying changes in market momentum.
## How to Use
🌊 Bullish Crossover
When X1 (Aqua) crosses above X2 (Orange), an Aqua ball appears.
This event represents a potential shift in momentum to the upside and can be used as a reference when analyzing possible bullish movements.
🔻 Bearish Crossover
When **X1 (Aqua)** crosses below **X2 (Orange)**, a **red-orange ball** appears.
This event represents a potential shift in momentum to the downside and can be used as a reference when analyzing possible bearish movements.
Reference Zones
The indicator includes two main reference zones:
* Above +60: elevated momentum zone.
* Below -60: negative momentum zone.
* Between +60 and -60: intermediate momentum zone.
These zones should not be interpreted independently as automatic buy or sell signals. They are intended to provide additional context when evaluating momentum.
## X1-X2 Area
The area between X1 and X2 helps visualize the difference between the two waves:
* Green: X1 is above X2.
* Red: X1 is below X2.
A wider separation between the waves indicates a larger momentary difference between fast momentum and its smoothed reference.
Settings
The indicator has two main parameters:
Fast Wave ⚡ — Default: 10
Controls the responsiveness of the fast wave.
Slow Wave 🐌 — Default: 21
Controls the smoothing of the reference wave.
Lower values may make the indicator more responsive to market changes, while higher values generally produce a smoother reading.
Suggested Use
Wave-Ocean Trend can be used together with:
* Market structure
* Support and resistance
* Higher-timeframe trend
* Volume
* Price action
* Risk management
One possible approach is to identify the broader trend on a higher timeframe and then use Wave-Ocean Trend crossovers on a lower timeframe to evaluate momentum within that context.
Important
Wave-Ocean Trend is a **technical analysis tool and does not guarantee financial results.
No crossover should be considered, by itself, a recommendation to buy or sell. Signals may occur during consolidation, choppy markets, or periods of high volatility and should be evaluated within the broader market context.
Use proper risk management and perform your own testing before using the indicator in live trading.
Indikator
Regime Gated Confluence Score [Pineify]Regime Gated Confluence Score
Overview
This pane indicator combines trend, momentum, and volume after a four-state gate selects meaning and weight. The main score and dashboard reconcile signed contributions.
Problem Definition
Fixed-weight confluence hides a regime error. Positive RSI may confirm a trend but mark extension in a range. EMA separation can persist after efficient travel ends. Relative volume shows participation, not acceptance. A permanent sum can stay strong when path efficiency is low, factors disagree, or ATR leaves its baseline, so users cannot tell whether magnitude reflects agreement or one dominant input.
Design Rationale
ATR-normalized EMA separation and slope measure trend across price scales. Centered RSI supplies momentum; RANGE reverses it to express a fade. Volume pressure combines capped relative volume with close location without claiming aggressor flow. EMA spread and path efficiency classify structure; ATR versus baseline identifies displacement. Lower hold thresholds add hysteresis. A trained model would add hidden data assumptions, while fixed weights preserve the failure. Explicit rules accept sensitivity and lag for auditability.
Key Features
Four regimes with hysteresis.
Standardized trend, RSI, and participation factors.
Regime weights, range inversion, missing-volume renormalization, conflict attenuation, exact contribution totals, and confirmed alerts.
How It Works
EMA spread and fast-EMA change are normalized by ATR, blended 65/35, and clipped to -1 through +1. RSI is centered at 50, divided by 25, and clipped. Volume multiplies close location inside the bar by relative volume capped at 2.5 times baseline, then smooths it. If fewer than 80% of volume-window bars are usable, volume is omitted.
Trend strength is absolute normalized EMA spread. Path efficiency divides net movement by total one-bar movement. ATR relative to baseline measures displacement. VOLATILE has priority until its lower hold level clears. Otherwise, strong separation and efficiency enter TREND, weak evidence enters RANGE, and unresolved evidence is TRANSITION.
Trend/momentum/volume weights are 55/30/15 in TREND, 15/60/25 in RANGE, 40/35/25 in VOLATILE, and 35/40/25 in TRANSITION. RANGE reverses only RSI. Missing volume removes its weight and renormalizes the others. Agreement divides absolute net contribution by total absolute contribution and sets a 0.55-to-1 gate; VOLATILE adds an ATR penalty. Gated components sum to the score. Warm-up or invalid threshold and EMA ordering blocks output with a diagnostic.
How Multiple Indicators Work Together
Trend estimates structure, momentum locates bounded pressure, and volume tests participation plus bar acceptance. The regime interprets them before combination. Without range inversion, extension becomes a continuation vote; without trend, brief momentum can dominate; without volume, weights must be renormalized. Agreement converts remaining conflict into lower magnitude rather than hiding it.
Trading Ideas and Insights
Use the score as context, not an order. A confirmed threshold cross during TREND identifies aligned conditions. In RANGE, check whether trend or volume opposes inverted momentum before considering a fade. In VOLATILE, a compressed gate shows ATR displacement discounting the raw sum. A strong component beside a modest total indicates conflict.
Unique Aspects
The contribution is the sequence of classification, interpretation change, weighting, and attenuation. RANGE reverses momentum while other factors can veto it; hysteresis separates trend entry from persistence; missing volume is removed; and agreement scales every component so the ledger equals the score. The halo shows magnitude, the background shows regime, and the table exposes construction.
How to Use
Start with defaults and compare the regime label with visible path behavior. Wait for warm-up. Keep the ledger visible to see whether structure, oscillator pressure, or participation drives direction. Use confirmed alerts when closing-state transitions matter. Contribution lines are diagnostic; the halo and background form the primary view. Omitted volume means a disclosed two-factor score.
Customization
EMA lengths and slope lookback control structural response; RSI length controls momentum sensitivity. Volume baseline and smoothing trade speed for stability. Regime length changes path efficiency and the ATR baseline. Entry thresholds must exceed hold thresholds. Raising the score threshold reduces alert frequency but does not establish better forecasting. Visual switches change display only.
Assumptions and Limitations
The script uses chart OHLC and reported volume. Exchange, tick, and absent volume differ; close-location volume is only a proxy. EMA, ATR, RSI, and rolling baselines lag. RANGE can fade a breakout, hysteresis can delay exits, and attenuation can suppress an early shock.
Realtime factors, regime, colors, and score can change before close; alerts require confirmation. No request calls, future data, pivots, or negative offsets are used. The script does not model liquidity, news, sizing, entries, stops, or exits. Thresholds do not establish expected return. Sparse bars and unreliable volume can distort evidence.
Conclusion
This replaces a fixed sum with an inspectable state process. The score and ledger show weights, conflict attenuation, and missing-data effects. Keep separate risk and execution rules.
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Indikator
RC Tools - Divergence DetectorRC Tools — Divergence Detector
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█ OVERVIEW
Most divergence tools pattern-match swing highs and lows, which is finicky and often technically repaints — pivots can un-confirm as new bars form. This tool instead measures rolling correlation between price and a momentum oscillator of your choice. When price and momentum stop agreeing, that disagreement is the divergence — measured continuously, not detected as a one-off pattern.
█ WHAT IT DOES
Plots the rolling correlation between price and a selectable oscillator (RSI, MACD line, Rate of Change, or a custom source) on a -1 to +1 scale. Classifies each confirmed bar into one of three states — Confirmed Trend, Bearish Divergence, Bullish Divergence — colours the chart background accordingly, and shows a table with the current state, how long price has been in it, and historical base rates (average forward return and win rate) for each divergence state.
█ THE THEORY BEHIND IT
A genuine trend has price and momentum moving together — new highs accompanied by strengthening momentum, new lows by weakening momentum. When that relationship breaks down — price continues in one direction while the oscillator stops confirming it — that is a divergence. Rather than searching for specific swing-point patterns (which depend on exactly which pivots you pick and can shift as price continues), this tool asks the more direct statistical question: over the last N bars, how closely have price and the oscillator actually moved together? A strong positive correlation means they agree. A correlation that has dropped toward zero or negative means they have stopped agreeing, regardless of what any single pivot looks like.
█ HOW IT IS CALCULATED
1. Compute the selected oscillator: RSI, MACD line (fast EMA minus slow EMA), Rate of Change %, or a custom source you provide.
2. Compute the rolling Pearson correlation between price (close) and the oscillator over a configurable window (default 14 bars).
3. If that correlation falls below a threshold (default 0.0), price and momentum are no longer confirming each other — a divergence state.
4. The divergence is labelled Bearish if price has been rising over a short lookback (momentum failing to confirm continued strength) or Bullish if price has been falling (momentum failing to confirm continued weakness).
Classification occurs ONLY on confirmed bar close — the state and the displayed correlation are computed and committed together, so they can never disagree mid-bar or flip back and forth as the current bar forms.
█ SETTINGS & CONFIGURATION
• Oscillator (default RSI) — RSI / MACD Line / Rate of Change % / Custom Source
• RSI / MACD / Rate of Change lookbacks (defaults 14 / 12+26 / 20)
• Correlation Window (default 14 bars) — how far back the co-movement is measured
• Divergence Threshold (default 0.0) — the correlation level below which price and momentum are considered to have stopped agreeing
• Price Direction Lookback (default 5 bars) — used only to label a divergence bullish or bearish
• Forward Return Window (default 20 bars) — the horizon used for the base-rate table
• Paint Main Chart Background — toggle off if you only want the correlation pane
█ HOW TO USE IT
Use it as a warning flag on an existing trend read, not as a standalone entry signal. Example: if you're long into a rally and the background flags Bearish Divergence, that's a cue to tighten risk management or look for confirmation elsewhere before assuming the move continues unchecked — it is not, by itself, a sell signal. Check the base-rate table's sample count before treating any single divergence reading as meaningfully predictive.
Works on any asset and timeframe with sufficient history for the correlation window.
█ LIMITATIONS
• Divergence describes a PRESENT disagreement between price and momentum. It does not predict a reversal, and any use of it as a forecast is a misuse.
• Correlation is measured over a rolling window and is noisy by nature — expect it to cross the threshold repeatedly in choppy, range-bound conditions.
• The oscillator itself is not plotted, only its correlation with price — this keeps the pane on one consistent scale regardless of which oscillator is selected (RSI is bounded 0-100, MACD line is unbounded, etc.).
• The bullish/bearish label depends on a short price-direction lookback, which can flip near genuine turning points independently of the correlation reading itself.
• Historical base-rate stats need a meaningful sample count (check N) before being trusted, especially for less common states.
• This script does NOT repaint. All classification updates on confirmed bar close only.
█ DISCLAIMER
For educational and informational purposes only. Nothing here is financial advice. Past behaviour of any divergence state does not indicate future results. Trade at your own risk.
Indikator
ADX / DMI(+)(-) TRENDICATOR## Draft Description
**ADX / DMI(+)(-) TRENDICATOR** is a responsive trend-strength and directional-momentum indicator designed to complement an **8 EMA / 20 EMA trading system**.
It combines:
- **ADX** to measure trend strength
- **DI+** to measure bullish directional pressure
- **DI−** to measure bearish directional pressure
- **20 and 40 ADX levels** to identify developing and strong trends
- **Angel Crosses** when DI+ crosses above DI−
- **Death Crosses** when DI− crosses above DI+
- Confirmed-candle alerts designed to avoid intrabar repainting
The default calculation settings use an **8-period DI length** and **8-period ADX smoothing** for a faster response to recent price candles. All calculation settings remain adjustable for different markets and timeframes.
The indicator includes customizable:
- ADX, DI+, and DI− visibility
- ADX and DI line widths
- Line, stepline, and circle plot styles
- Indicator colors
- Horizontal level visibility and styles
- ADX alert threshold
- Directional DI fill
Use ADX to determine whether a market is trending, then use DI+ and DI− to identify the dominant directional pressure. For example, a bullish EMA alignment combined with DI+ above DI− and ADX above 20 may indicate strengthening bullish momentum.
## How It Differs From Typical ADX/DMI Indicators
### 1. Confirmed-candle behavior
Many indicators react to changing intrabar values, causing temporary crosses or signals that can disappear before the candle closes. This indicator commits ADX, DI+, and DI− values only after candle confirmation, helping prevent intrabar signal repainting.
### 2. Designed for faster EMA-based systems
The default **8/8 settings** are intended as a responsive starting point for an **8 EMA / 20 EMA trend system**, rather than relying exclusively on the traditional slower 14/14 settings.
### 3. Clearer trend-strength framework
The fixed **20 and 40 levels** provide a simple visual framework:
- Below 20: weak or ranging conditions
- Above 20: trend development or moderate strength
- Above 40: strong trend conditions
### 4. More complete customization
Instead of only changing colors, users can control visibility, line widths, plot styles, level styles, and directional fills directly from the settings panel.
### 5. Expanded alert system
The indicator includes confirmed alerts for:
- Angel Crosses
- Death Crosses
- ADX crossing above or below 20
- ADX crossing above or below 40
- ADX crossing the custom alert threshold
### 6. Direction and strength are separated
Unlike systems that treat ADX as a buy or sell signal, this indicator keeps the concepts separate:
- **ADX = strength**
- **DI+ / DI− = direction**
- **8 EMA / 20 EMA = trend structure**
This helps reduce the common mistake of interpreting a rising ADX alone as a bullish signal. Indikator
QQE Trend Confluence [MarkitTick]💡 A dual-engine QQE (Quantitative Qualitative Estimation) confluence oscillator that layers eight selectable pre-smoothing algorithms, a secondary confirmation QQE pair, ADX and higher-timeframe bias gating, and a fully automated ATR-based trade planner with webhook-ready alert payloads on top of the classic Wilder RSI-trailing-stop concept.
✨ Originality and Utility
This script does not simply reproduce the stock QQE oscillator. It restructures the calculation into a layered decision pipeline where a signal only qualifies after passing through several independent, user-toggleable filters, turning a single momentum flip into a multi-factor confluence check.
The source price is first routed through a selectable pre-smoothing stage offering eight distinct algorithms, ranging from classic moving averages to a proprietary slope-projection method and a recursive Kalman estimator, before it ever reaches the QQE math. This changes the responsiveness and noise profile of every signal generated downstream.
A second, independently parameterized QQE instance runs in parallel purely as a confirmation gate, meaning a raw crossover on the primary pair is discarded unless a slower QQE pair already agrees with its direction.
An ADX/DMI strength filter and a non-repainting higher-timeframe bias filter can each independently veto a signal, so traders can require trend strength and multi-timeframe agreement without writing their own confluence logic.
The script goes beyond signal generation into trade management: a built-in ATR trade planner converts a qualifying cross into a full stop-loss and three-tiered take-profit plan, drawn directly on the chart and tracked bar by bar.
A structured JSON alert payload system is built into every signal and trade-management event, making the tool usable as the signal engine for an external automation or webhook pipeline without any manual message formatting.
The combination of these components is deliberate rather than incidental: the pre-smoothing stage shapes what "signal" means, the dual-QQE and filter stack decides which of those signals are trustworthy, and the trade planner and alert system decide what to do once a signal is accepted. Removing any one layer would leave a materially different and less complete tool, which is why they are published together as a single confluence system rather than as separate scripts.
🔬 Methodology and Concepts
• Adaptive Pre-Smoothing Engine
Before the source price reaches the QQE engine, it can optionally be passed through one of eight smoothing or prediction methods, selectable from a dropdown. This determines how "clean" or "responsive" the underlying momentum reading is.
Simple, Exponential and Wilder (RMA) moving averages behave as their standard definitions.
A double weighted moving average applies a WMA to the result of a first WMA pass, compounding the weighting effect for extra lag reduction.
A triple volume-weighted moving average chains three successive VWMA passes, folding volume into the trend estimate at each stage.
The Hull Moving Average uses the standard weighted-difference technique to reduce lag relative to a simple weighted average.
The proprietary LLAMA method computes a simple moving average baseline over the lookback window, then measures the linear slope of price across that same window (the difference between the current source and the value from "length" bars back, divided by length). That slope is then projected forward by half the lookback length and added to the SMA baseline. The practical effect is a moving average that leans ahead of price during a steady trend and collapses back toward a standard SMA when price is flat or choppy.
The Kalman Filter option treats the source price as a noisy observation of an underlying "true" trend state. It maintains an internal estimate and error variance, computes a Kalman gain each bar from a length-derived process-noise assumption and a fixed measurement-noise assumption, and blends the new price observation into the estimate proportionally to that gain, producing a smoothing curve that adapts its own responsiveness over time.
• Dual QQE Core
The QQE concept itself works by smoothing an RSI reading with an EMA, then measuring the average magnitude of bar-to-bar changes in that smoothed RSI (a Wilder-style double-smoothed "ATR of RSI"), and multiplying it by a factor to build a trailing envelope around the smoothed RSI line. This trailing level only moves in the direction the RSI is already travelling and locks in place, ratchet-style, whenever RSI reverses, similar in spirit to a classic ATR trailing stop but applied in RSI space rather than price space. A cross of the smoothed RSI over or under this trailing level marks a momentum shift. This script runs two such QQE instances simultaneously: a faster primary pair that generates the raw crossover, and an optional slower secondary pair whose sole purpose is confirmation, a signal from the primary pair is only accepted if the secondary pair's RSI-to-trail relationship already agrees with the same direction.
• Confirmation Filters
An optional ADX/DMI filter, built on Wilder's Average Directional Index, requires trend strength to be above a user-defined threshold before a signal is allowed through, filtering out crosses that occur during flat, directionless conditions.
An optional higher-timeframe bias filter pulls the same QQE relationship (smoothed RSI versus trailing level) from a user-selected higher timeframe and requires it to agree with the direction of the current-timeframe signal. This request is built using the previous, already-confirmed value on the higher timeframe combined with lookahead-on merging, which is the standard non-repainting pattern for higher-timeframe data: the value shown on any historical bar is the same value that would have been available to a trader watching in real time.
• ATR-Based Trade Planner
Once a signal clears every enabled filter, the script computes a stop-loss using the 14-period Average True Range multiplied by a user-defined multiple, anchored to the prior bar's close. Three take-profit levels are then derived from that risk distance using independently configurable risk:reward ratios. These levels are drawn as extending price lines with labels and shaded risk/reward zone fills, and the script continuously checks, bar by bar, whether price has touched each take-profit or the stop-loss, retiring the plan once the final target or the stop is hit. A lock control can freeze the currently displayed plan so it does not get replaced by a new signal while a trade is being managed.
• Signal Confirmation Behavior
The crossover state that drives every signal is always evaluated using the prior, already-completed bar's smoothed RSI and trailing-level relationship rather than the still-forming current bar. In practical terms, this means a BULL or BEAR marker only ever prints once the underlying cross is confirmed, and it does not shift position or disappear on subsequent price updates within the same bar.
• Automation-Ready Alerts
Every entry, exit, and trade-management event (long entry, short entry, close-long, close-short, and each of the three take-profit levels plus stop-loss) is wrapped in its own alert condition and also emits a structured JSON message through a single dynamic alert call, gated to fire only once per confirmed bar close for entries. Each JSON message includes the instrument, timeframe, and an editable action keyword, allowing the same signal engine to be wired directly into an external automation or webhook workflow.
🎨 Visual Guide
In the indicator's own pane: the blue RSI MA line is the primary smoothed-RSI reading, the yellow Smoothed Trail line is its dynamic trailing envelope, and the histogram plotted around the zero line reflects the distance between the two, colored teal on the bullish side and red on the bearish side.
Dashed reference lines at 70 and 30 mark overbought and oversold RSI zones with a light shaded fill between each level and the 50 midline when enabled.
On the price chart itself: candles can be recolored using a four-tone scheme, strong bullish teal and weak bullish dark teal, or strong bearish red and weak bearish dark red, with a neutral gray used whenever the current QQE distance is smaller than its own running average, giving an at-a-glance read on momentum strength as well as direction.
BULL and BEAR labeled arrows print just below or above the triggering candle whenever a fully confirmed signal fires.
When trade levels are enabled, dashed lines and small labels for the stop-loss, entry, and three take-profit levels extend to the right from the signal bar, with the area between entry and stop shaded as a risk zone and the area between entry and the furthest target shaded as a reward zone.
An optional multi-row dashboard panel, placeable in any chart corner, summarizes the instrument and timeframe, lock status, current bias, the raw RSI MA and Trail Level values, an ASCII progress-bar style RSI strength meter, the secondary confluence state, the higher-timeframe bias, the ADX reading and pass/fail color, the currently active pre-smoothing method, the ATR value, the DI+/DI- readings, a momentum strength bar, and the active trade's direction and price levels.
📖 How to Use
Treat a BULL or BEAR arrow as the point where every enabled filter, the primary cross, the secondary QQE confirmation, the ADX gate, and the higher-timeframe bias, has already agreed on a direction.
Use candle color intensity and histogram height as a secondary read on how strong the current momentum reading is relative to its own recent average, rather than as a standalone signal.
Scan the dashboard's Bias, Confluence, and HTF Bias rows for a fast multi-factor summary without needing to inspect the oscillator pane directly.
Enable the trade levels option to have the script draw a stop-loss and three take-profit targets automatically on each qualifying signal, and use the lock control to freeze that plan in place while managing an open position.
Adjust the ATR stop multiple and the three risk:reward ratios to match your own risk tolerance before relying on the drawn levels.
For automation, create a TradingView alert using the "Any alert() function call" option to receive the full JSON payload stream, or use the individual named alert conditions if only a single event type is needed.
This tool is a momentum and confluence framework, not a complete trading system on its own. Combine it with your own market structure, support/resistance, or volatility context before acting on any signal.
⚙️ Inputs and Settings
Core Settings: RSI Length and RSI EMA Smoothing control the primary QQE's momentum lookback and responsiveness; QQE Factor scales how wide the trailing envelope sits from the smoothed RSI; Source selects the price series feeding the whole calculation; the secondary QQE toggle, along with its own EMA smoothing and factor, controls the confirmation pair.
Filters: the ADX toggle, length, and threshold control the trend-strength gate; the Adaptive Filter dropdown and length select which of the eight pre-smoothing methods (including LLAMA and the Kalman Filter) is applied to price before the QQE math runs; the HTF filter toggle and timeframe control the higher-timeframe bias confirmation.
Trade Tools: toggles for showing trade levels and locking the current signal, an ATR multiple for stop-loss distance, and three independent risk:reward ratios for the three take-profit targets.
Visuals: independent toggles for the overbought/oversold zone fill, the histogram, the crossover arrows, and the color-matched candles.
Dashboard: a toggle to show or hide the panel and a dropdown to choose which chart corner it docks to.
Alerts: editable text fields defining the action keyword sent in the JSON payload for each of the eight tracked events, letting the output match whatever automation platform is receiving it.
Colors: a full set of color pickers covering the oscillator lines, histogram, zones, arrows, candle tones, trade-planning lines and fills, and dashboard styling, purely cosmetic and with no effect on calculations.
🔍 Deconstruction of the Underlying Scientific and Academic Framework
The foundation of the oscillator is J. Welles Wilder Jr.'s Relative Strength Index and his broader family of smoothed volatility and trend-strength tools, including the Average True Range concept and the Average Directional Index used here as an optional filter.
The QQE structure itself extends Wilder's trailing-stop logic, normally applied to price, into RSI space: an ATR-style measure of RSI's own volatility is used to build a ratcheting trailing envelope around the smoothed RSI line, conceptually related to other ATR-trailing-stop tools such as Chandelier Exit or SuperTrend but operating on a momentum oscillator rather than raw price.
The Hull Moving Average option is built on Alan Hull's weighted-difference technique for reducing the inherent lag of weighted moving averages.
The LLAMA pre-smoothing option applies a basic linear extrapolation principle, projecting a simple moving average forward using the measured slope of price across the same lookback window, a lightweight analogue of trend-extrapolation methods used in linear regression forecasting.
The Kalman Filter option is a direct application of Rudolf Kálmán's recursive estimation framework, treating price as a noisy observation of an unobserved underlying trend state and updating that estimate bar by bar using a dynamically computed gain, a technique widely used in modern adaptive filtering and signal processing.
The ATR trade planner applies standard volatility-based position planning, using a multiple of Average True Range to size a stop distance and deriving profit targets from fixed risk:reward multiples of that same distance.
⚠️ Disclaimer
All provided scripts and indicators are strictly for educational exploration and must not be interpreted as financial advice or a recommendation to execute trades. We expressly disclaim all liability for any financial losses or damages that may result, directly or indirectly, from the reliance on or application of these tools. Market participation carries inherent risk where past performance never guarantees future returns, leaving all investment decisions and due diligence solely at your own discretion. Indikator
Multi-MA Trend Ribbon [MarkitTick]💡 A fully adaptive moving-average ribbon that lets you choose from 30 different smoothing algorithms — from classic SMA/EMA to advanced adaptive filters like Kalman, JMA, KAMA, and a custom volatility-responsive method called LLAMA — then builds a multi-line, gradient-colored trend ribbon out of that single chosen method across up to 8 progressively longer lengths. Layered on top is an optional multi-timeframe bias filter, an ADX strength gate, a volume confirmation gate, webhook-ready JSON alerts, and a live diagnostic dashboard.
✨ Originality and Utility
Most ribbon-style indicators on the platform hard-code a single averaging method (usually EMA or HMA) and stack a handful of fixed lengths on the chart. This script takes a different approach: it treats the "ribbon" as a generic container and the "moving average type" as a fully interchangeable engine, with 30 distinct algorithms available from a single dropdown, all built from first principles (not by calling a bundle of pre-packaged libraries). Because every ribbon line is generated by the same underlying function at different lengths, switching the MA Type instantly re-renders the entire ribbon in the new smoothing style, giving traders a single tool to compare how trend-following behaves under drastically different mathematical assumptions (linear vs. exponential weighting, adaptive vs. fixed responsiveness, zero-lag vs. standard lag) without switching indicators.
The script's originality centers on three custom-built components not found in standard built-ins:
A proprietary adaptive length mechanism ("LLAMA") that dynamically expands or contracts each ribbon line's effective lookback based on a short-term directional forecast, rather than using a static length.
A dual-RSI-divergence-weighted directional predictor that feeds that adaptive length engine.
A from-scratch implementation of less commonly available filters (Kalman, JMA, FRAMA, T3, McGinley, Super Smoother) that are not native Pine built-ins, giving traders access to algorithms usually reserved for institutional charting platforms or custom research code.
The mashup of a trend ribbon, a confluence filter stack (ADX + HTF + Volume), and a webhook alert system is justified because these three layers solve three different practical problems traders face together: identifying trend direction (ribbon), avoiding low-quality signals in choppy or thin conditions (filters), and automating execution (alerts) — components that are commonly used in sequence by discretionary and systematic traders alike, making their integration into one tool a genuine workflow simplification rather than an arbitrary bundling.
🔬 Methodology and Concepts
● Core Ribbon Construction
The script computes eight moving averages of the same source (default: close) at lengths that increase by a fixed step from a base length. For example, with a Base of 20 and a Step of 10, the eight lengths used are 20, 30, 40, 50, 60, 70, 80, and 90. The fastest line (MA1) and the slowest visible line (determined by the Lines setting) are compared: when the fast line sits above the slow line, the ribbon is considered to be in a bullish regime; when below, bearish. All eight lines are generated by the exact same averaging function, so the "shape" of the ribbon (how tightly or loosely the lines fan out) becomes a visual proxy for trend strength and consistency across time horizons.
● Selectable Smoothing Engine
The Type input lets you choose the mathematical method used to compute every single line in the ribbon simultaneously. The available families are:
Classic weighted averages: SMA, EMA, RMA (Wilder's smoothing), WMA, Triangular (TRIMA), Volume-Weighted (VWMA), and their double/triple-smoothed variants (DWMA/TWMA, DVWMA/TVWMA) which apply the same weighting function recursively to reduce lag-vs-noise trade-offs.
Zero/reduced-lag filters: Hull MA (HMA) and its extended variants EHMA and THMA, DEMA and TEMA (double/triple exponential smoothing, per Patrick Mulloy's original error-correction concept), and ZLEMA (zero-lag EMA using a momentum-shifted input).
Adaptive/volatility-responsive filters: KAMA (Kaufman's Adaptive MA, which speeds up or slows down based on an efficiency ratio of net movement to total movement), VIDYA (Chande's Variable Index Dynamic Average, which scales its responsiveness using Chande Momentum Oscillator readings), FRAMA (Ehlers' Fractal Adaptive MA, which estimates a fractal dimension from recent high/low ranges to adjust smoothing), and JMA (a Jurik-style adaptive filter using a two-stage predictive/corrective recursive structure).
Specialized/legacy filters: T3 (Tillson's six-pole exponential blend using a volume factor to control overshoot), McGinley Dynamic (a self-adjusting average that speeds up during fast markets and slows down during consolidation via a ratio-based denominator), ALMA (Arnaud Legoux MA, a Gaussian-weighted average with adjustable offset and smoothness), LSMA (least-squares linear regression endpoint), SWMA (a fixed symmetric 4-bar weighted average), Median, and SSF (a two-pole Super Smoother Filter using an Ehlers-style recursive IIR design).
Proprietary adaptive engine — LLAMA: A custom exponential filter whose smoothing constant is derived not from a fixed length, but from a dynamically computed effective length (see below).
• LLAMA and the Directional Predictor
LLAMA (the script's custom adaptive method) works in two stages. First, a directional forecast is built from two RSI readings (14-period and 28-period). Over a lookback window, each prior bar is scored by how closely its RSI signature matches the current bar's RSI signature (using a log-distance similarity weighting), and that similarity is used to weight whether price rose or fell on that historical bar. The weighted average of those historical outcomes produces a forecast value between -1 (strongly bearish precedent) and +1 (strongly bullish precedent). Second, that forecast value is used to stretch or compress each ribbon line's effective length within a configurable percentage range around its base length — a stronger bullish or bearish forecast pushes the effective length toward one end of the range, changing how reactive that specific line is to new price action. This effective length is then converted into a standard exponential smoothing constant to produce the final LLAMA value. The result is a moving average that behaves less like a fixed-parameter tool and more like a filter that continuously recalibrates its own sensitivity based on recent directional evidence.
● Trend Signals
Two categories of signals are generated:
Ribbon Flips: Triggered when the relationship between the fastest line and the slowest visible line changes state (fast crosses from below to above the slow line, or vice versa), using confirmed prior-bar values to avoid intrabar flicker.
Price Crosses: Triggered when price itself crosses the fastest ribbon line (MA1), independent of the broader ribbon state, offering an earlier but noisier entry cue.
● Confluence Filters
Three optional, independently toggleable filters can be layered onto both signal types to suppress low-quality triggers:
ADX Strength Filter: Requires Wilder's Average Directional Index (calculated via the standard DMI/ADX formula) to be above a minimum threshold before a signal is allowed to fire, filtering out signals generated during weak or range-bound conditions.
Higher-Timeframe Bias Filter: Recomputes the entire ribbon logic (fast MA vs. slow MA) on a user-selected higher timeframe and requires the current-timeframe signal to agree with that higher-timeframe bias before firing. This uses a confirmed prior-bar value pulled via request.security() with lookahead explicitly enabled on historical (already-closed) data only, so no future information leaks into the calculation.
Volume Confirmation Filter: Requires the prior bar's volume to exceed a multiple of its recent average volume, ensuring signals are backed by above-average participation rather than occurring on thin, low-conviction bars.
🎨 Visual Guide
Ribbon Lines (MA1–MA8): Up to eight plotted lines, one per configured length, colored on a gradient. When Trend Col is enabled, the gradient runs between your chosen Bull and Bear colors depending on the current trend state; when disabled, it instead runs between the Fast and Slow colors you've set, regardless of trend direction.
Ribbon Fill: The semi-transparent shaded area between each consecutive pair of ribbon lines, colored to match the current trend (bull or bear color) with adjustable transparency via the Fill Transparency setting. A tightly compressed, thin fill indicates the ribbon lines are converging (potential consolidation or transition); a wide, expanded fill indicates strong trend separation.
Bull/Bear Flip Markers: Small triangle shapes below or above the bars marking the exact bar where a confirmed Ribbon Flip occurred — an upward triangle in your Bull color for bullish flips, a downward triangle in your Bear color for bearish flips.
Heatmap Candles (optional): When enabled, replaces standard candle coloring with your chosen Bull/Bear body and border colors based on the ribbon's current trend state, turning the entire chart into an at-a-glance trend heatmap.
Dashboard Table: An on-chart panel (position configurable) summarizing, in real time: signal lock status, current bias, active MA type and lengths, a visual bar-graph readout of the number of active ribbon lines, the fast and slow MA values, the current spread between them, the LLAMA directional prediction strength, the most recent flip direction, the most recent price cross direction, how many filters are currently active, the live ADX reading, the +DI/-DI values, the current volume ratio versus average, and the higher-timeframe bias state.
📖 How to Use
Use the overall ribbon color and fill (bull color vs. bear color) as your primary trend read: a consistently bull-colored, moderately expanded ribbon suggests sustained upward momentum, while contraction or color-flipping suggests indecision.
Treat triangle Flip markers as your core trend-change signal — they only appear once the flip has been confirmed on a closed bar, and (if filters are enabled) only after passing your chosen strength, HTF-agreement, and volume conditions.
Treat Price Cross events (visible in the dashboard's "Price Cross" row) as a faster, more aggressive alternative entry cue for traders who want to react before a full ribbon flip occurs, understanding this comes with a higher likelihood of false signals.
Enable the Lock Signal option to freeze the current bias and temporarily suspend new signal generation — useful when you want to hold a view steady while manually reviewing a setup instead of reacting to every subsequent flip.
Watch the dashboard's Filters and individual ADX / Vol Ratio / HTF Bias rows to understand in real time why a signal is or is not being permitted to fire.
Consider combining a slower Type (e.g., RMA, T3, or a longer-length adaptive filter) for the overall bias with faster Price Cross signals for tactical entries within that bias.
⚙️ Inputs and Settings
Type: Selects which of the 30 supported averaging methods is used to build every line in the ribbon.
Src: The price source fed into all calculations (default: close).
Base / Step: Base sets the length of the fastest ribbon line; Step sets the length increment applied to each subsequent line. Together they define the full spread of lengths across the ribbon.
Shift: Applies a horizontal bar offset to all plotted ribbon lines. A non-zero value shifts the visual plot forward or backward relative to price and does not alter the underlying calculation.
Lines: Sets how many of the eight possible ribbon lines are displayed (2–8), which also determines which line is treated as the "slow" reference line for bias and flip calculations.
ALMA Off / ALMA Sig, T3 Vf, KAMA Fast / KAMA Slow, JMA Phase / JMA Pow, Kal Q / Kal R, LLAMA LB / LLAMA Rng: Method-specific tuning parameters that only take effect when the corresponding Type is selected — these control offset/smoothness for ALMA, volume factor for T3, the fast/slow efficiency bounds for KAMA, phase/power for JMA, process/measurement noise for Kalman, and lookback/range for the custom LLAMA engine.
ADX / HTF / Vol toggles and their sub-settings: Independently enable and configure the three confluence filters described in the Methodology section (strength threshold and length for ADX, target timeframe for HTF, lookback length and multiplier for Volume).
Lock Signal: Freezes the currently displayed bias and suppresses new flip/cross signals until disabled.
Trend Col / Fill / Fill Transparency / Width / Bars / Signals: Visual controls for whether ribbon coloring reflects trend state, whether the fill between lines is shown and how transparent it is, line thickness, whether heatmap candles are shown, and whether flip markers are plotted.
Dashboard Show / Position: Toggles the on-chart dashboard and sets its screen position.
Alert toggles and Action fields: Enable/disable Flip-based and Cross-based alerts independently, and customize the text string sent in each alert's JSON payload for long entry, short entry, close-long, close-short, cross-up, and cross-down events — designed to be dropped directly into webhook-based automation.
⚠️ Confirmation Lag Notice
The Shift input allows ribbon lines to be plotted with a backward or forward bar offset relative to the current price bar. When a non-zero Shift value is used, what you see plotted at a given bar's x-position does not represent that bar's actual calculated value in real time — always verify the Shift setting is at its default (0) if you intend to use the ribbon for real-time signal interpretation, and be aware that a non-zero offset can visually misrepresent how early or late a line's response to price actually was.
🔍 Deconstruction of the Underlying Scientific and Academic Framework
This script draws on several distinct threads of technical and quantitative theory:
Classical trend-following theory: The core "fast MA vs. slow MA" bias mechanism traces back to Dow Theory's premise that trend direction can be inferred by comparing price behavior across different time horizons — approximated here by comparing smoothed averages of different lengths rather than raw price.
Exponential smoothing and digital filter theory: Methods like EMA, DEMA, TEMA, and ZLEMA build on Patrick Mulloy's work on reducing the inherent lag of exponential moving averages through cascaded and momentum-adjusted smoothing, itself grounded in classical infinite impulse response (IIR) filter design from signal processing.
Adaptive filter theory: KAMA (Kaufman), VIDYA (Chande), and FRAMA (Ehlers) all apply the same broader principle from adaptive control theory — that a filter's time constant should not be fixed but should respond to a real-time measurement of market "efficiency" or "noise," whether measured via a directional efficiency ratio, momentum oscillator magnitude, or fractal dimension of price geometry.
State-space estimation theory: The Kalman filter option applies the classical Kalman filtering framework from control and estimation theory — treating the true underlying trend as a hidden state to be recursively estimated from noisy price observations, balancing a process-noise parameter (how much the true state is expected to drift) against a measurement-noise parameter (how much to trust each new observation).
Fractal market theory: FRAMA's dimension calculation is grounded in Mandelbrot's fractal geometry concepts as adapted by John Ehlers, using the scaling relationship between price range measured at different resolutions to infer whether the market is behaving more like a trending (lower fractal dimension) or random-walk (higher fractal dimension) process.
Directional Movement / trend strength theory: The ADX filter implements Welles Wilder's original Directional Movement System, which decomposes price movement into positive and negative directional components and derives a smoothed strength index from their divergence.
Weighted similarity / kernel-based forecasting: The custom LLAMA predictor's weighting scheme is conceptually related to kernel-weighted (locally weighted) regression and nearest-neighbor forecasting methods, in which historical observations are weighted by their similarity to current conditions (here, measured via RSI-signature distance) rather than treated with uniform recency weighting.
⚠️ Disclaimer
All provided scripts and indicators are strictly for educational exploration and must not be interpreted as financial advice or a recommendation to execute trades. We expressly disclaim all liability for any financial losses or damages that may result, directly or indirectly, from the reliance on or application of these tools. Market participation carries inherent risk where past performance never guarantees future returns, leaving all investment decisions and due diligence solely at your own discretion. Indikator
RS Leader - Early Breakout RadarRS Leader - Early Breakout Radar identifies stocks demonstrating exceptional relative strength before a conventional price breakout occurs.
The indicator compares the current symbol with a selectable market benchmark, using SPY by default. It searches for situations in which the relative-strength ratio is near a long-term high while the stock remains in a tight consolidation beneath its previous price high. This combination can help identify securities outperforming the broader market before that leadership becomes obvious from price alone.
RS Leader is different from the RSI oscillator. Its relative-strength calculation is:
Stock Price ÷ Benchmark Price
RS Leader Score
Each stock receives a dynamic score from 1 to 100:
• Relative-strength leadership: 40 points
• Proximity to the breakout level: 20 points
• Price-range contraction: 15 points
• Moving-average structure: 15 points
• Volume behavior: 10 points
A default minimum score of 70 is required before an RS Leader signal can appear. All requirements and scoring thresholds can be adjusted in the indicator settings.
Signal Interpretation
• Blue RS LEADER label: Relative strength is near a long-term high while price remains tightly consolidated below resistance.
• Blue line: The nearby price level that must be exceeded for a potential breakout.
• Green BREAKOUT label: Price closed above the prior resistance level following an active RS Leader setup.
• Blue background shading: Optional highlighting of bars that currently satisfy the complete setup.
Dashboard Colors
• Green: Condition is favorable or confirmed.
• Blue: An active RS Leader setup meets the minimum score.
• Orange: Condition is developing, neutral or requires caution.
• Red: Condition is not currently satisfied.
The dashboard displays the current RS Leader Score, relative-strength status, distance from the price high, consolidation width, moving-average alignment, relative volume and selected benchmark.
The indicator uses confirmed closing-bar information and does not intentionally use future data. Signals can still fail, and historical relationships do not guarantee future results. Relative strength may deteriorate, apparent breakouts may reverse, and market or company-specific events can materially affect price behavior.
RS Leader is provided solely for educational and informational purposes. It does not constitute investment advice, a recommendation to buy or sell any security, or a guarantee of future performance. Users should independently evaluate market conditions, liquidity, earnings dates, volatility and personal risk tolerance before making any financial decision. Indikator
Indikator
ATR Deviation OscillatorATR Deviation Oscillator
The ATR Deviation Oscillator is a simple ATR-based volatility, price deviation, and market momentum indicator that measures how far price has moved away from its moving average, normalized by Average True Range (ATR).
Instead of using raw price distance, it shows the deviation in ATR units, making it easier to identify price expansion, volatility, trend strength, momentum, overextension, and potential mean-reversion areas across different market conditions.
How It Works
The core calculation is:
(Price - Moving Average) / ATR
This produces a normalized oscillator centered around zero.
0 — Price is at the moving average.
Positive values — Price is above the baseline.
Negative values — Price is below the baseline.
+1 / -1 ATR — Price is approximately 1 ATR from the baseline.
+2 / -2 ATR — Price is approximately 2 ATR from the baseline.
+3 / -3 ATR — Price is approximately 3 ATR from the baseline.
ATR Deviation Levels
The 1, 2, and 3 ATR levels help visualize how extended price is relative to its current volatility.
Higher readings can indicate strong price momentum, trend expansion, volatility expansion, or overextension.
Lower readings can indicate downside momentum, trend weakness, volatility expansion, or potential oversold/mean-reversion conditions.
These levels are not fixed percentage thresholds. They automatically adapt to current market volatility through ATR.
Moving Average Options
Choose from:
SMA — Simple Moving Average
EMA — Exponential Moving Average
RMA — Relative Moving Average
WMA — Weighted Moving Average
VWMA — Volume Weighted Moving Average
This allows the oscillator to be adapted to different trading strategies, market conditions, timeframes, and instruments.
What You Can Use It For
The ATR Deviation Oscillator can help with:
ATR volatility analysis
Price deviation analysis
Trend strength
Momentum analysis
Market overextension
Mean reversion
Volatility expansion
Breakout analysis
Pullback analysis
Moving average distance
Price momentum
Trend continuation
Potential reversal zones
Overbought and oversold conditions
Market regime analysis
The indicator can be useful for Forex, Gold, Crypto, Stocks, Indices, Futures, and other liquid markets.
Important
The ATR Deviation Oscillator is a market analysis tool, not a standalone buy or sell signal. Extreme deviation does not automatically mean price will reverse. Strong trends can remain extended for long periods.
Use the oscillator together with price action, market structure, trend analysis, support and resistance, volatility, and your existing trading strategy. Indikator
Adaptive Composite Oscillator (ACO)Adaptive Composite Oscillator (ACO)
A momentum oscillator that adapts its own lookback length, normalization bands, and signal logic to current market conditions, rather than relying on the fixed parameters and fixed 70/30-style bands used by traditional oscillators like RSI or Stochastic.
How it works
1. Adaptive lookback. The effective momentum length shortens when recent volatility (ATR relative to its own average) is elevated, and lengthens when volatility is calm. The oscillator speeds up in choppy or volatile stretches and slows down in quiet ones, instead of using one fixed period regardless of context.
2. Manual adaptive RSI. Pine's built-in ta.rsi() requires a fixed length, which a bar-by-bar adaptive length can't satisfy. So the RSI is built manually with a Wilder-style recursive average whose smoothing factor is derived from the adaptive length on every bar — same underlying math as RSI, just computed in a way that tolerates a variable length.
3. KAMA-style smoothing. The raw adaptive RSI is passed through a Kaufman Adaptive Moving Average-style filter, using an efficiency ratio between fast and slow EMA constants. This makes the line track efficient, directional moves closely while damping down noise during back-and-forth chop.
4. Statistical normalization. Rather than fixed overbought/oversold levels, the smoothed momentum is converted into a z-score against its own rolling mean and standard deviation. The ±2 SD bands self-calibrate to each instrument's own volatility character instead of using one arbitrary threshold for every market.
5. Regime filter (ADX/DMI). An ADX reading classifies conditions as ranging or trending. In ranging conditions, z-score extremes are treated as mean-reversion signals. In strong trends (ADX above threshold), those same extremes are deliberately ignored — since momentum can stay "overbought" for a long time inside a real trend — and instead a zero-line cross in the direction confirmed by +DI/−DI is treated as a trend-continuation signal.
6. Volume confirmation. Every signal additionally requires volume above its own moving average, filtering out low-participation moves that wouldn't hold up.
7. Algorithmic divergence with connecting lines. Bullish and bearish divergence is detected by comparing confirmed price pivots to oscillator pivots — a defined rule, not a discretionary read — and drawn as connecting lines on both the price chart and the oscillator pane, so the actual shape of the divergence is visible rather than marked with a single dot.
What's plotted
Oscillator line (z-score), colored by regime — gray for ranging, blue for confirmed uptrend, orange for confirmed downtrend
Dashed ±2 SD statistical bands and a zero line
Yellow background shading while in a strong-trend regime
Green/red triangles for volume-confirmed long/short signals
Magenta/lime connecting lines for bearish/bullish divergence, on both panes
How to use it
Start by reading the regime background: yellow shading means the market is trending strongly by ADX; no shading means it's ranging. That tells you which of the two signal modes is currently active. Then read the line color — gray, blue, or orange — which tells you the direction of any active trend. Triangles mark volume-confirmed signals: green below the line for long, red above for short. Connecting lines mark divergence: magenta between two price/oscillator highs for bearish, lime between two lows for bullish — these appear a few bars after the second pivot confirms, since a pivot needs bars on both sides to validate.
The strongest setups combine elements rather than relying on one signal alone — for example, a long triangle firing alongside a lime divergence line, or a trend-mode zero-cross that agrees with a higher-timeframe trend you've checked separately. Avoid taking ranging-mode mean-reversion signals against a clearly shaded trending background — that's exactly the mismatch the regime filter exists to prevent.
All lengths, the ADX trend threshold, volume multiplier, pivot lookback, and KAMA constants are adjustable in settings; the defaults are a reasonable starting point, not a finished strategy. Four alert conditions are built in (Long Signal, Short Signal, Bullish Divergence, Bearish Divergence) via TradingView's standard Add Alert dialog. Indikator
VWAP Rope Band by ByblloVWAP Rope Band plots a smoothed trend line (the "rope") that only moves once price has traveled beyond a VWAP-deviation threshold from its last position - small back-and-forth noise around VWAP is absorbed, and the line only steps when a move is statistically meaningful.
The threshold is the standard deviation of (close - VWAP) over a lookback period, scaled by a multiplier, so the surrounding band automatically widens or narrows with how far price is currently dispersing from VWAP - no manual adjustment needed as volatility changes.
A genuine trend reversal is only registered once the rope actually reverses direction (not on every VWAP wiggle). That short transition window gets its own color, an optional gradient cloud, and an optional Buy/Sell badge at the exact bar the reversal is confirmed.
INTENDED USE
Works well for short-term futures scalping - Nasdaq futures, KOSPI200 futures, and similar instruments. Built and tested primarily on the 1-minute chart, but the underlying VWAP/rope/band logic is timeframe-agnostic and holds up well on 2, 3, and 5-minute charts and other intraday timeframes too. The StdDev Length and Band Multiplier adapt to volatility automatically, but it's worth rechecking them when you switch timeframe or instrument.
FEATURES
- Threshold-based "rope" trend line that ignores VWAP noise, only stepping on statistically meaningful deviations
- Volatility-adaptive band (self-widening/narrowing standard-deviation envelope around the rope)
- True-gradient cloud fill between rope and band, with adjustable steepness
- Confirmed-reversal transition detection with its own color/cloud, auto-expiring after 5 bars if unresolved
- Optional Buy/Sell badge plotted at the exact bar a reversal is confirmed
- Two alert families: simple rope crossover/crossunder, and confirmed Buy/Sell signal alerts
- Works on any chart type (candlestick, Heikin Ashi, Renko, etc.) since prices are pulled via request.security() from the underlying ticker
This is a visual/alerting tool only - it does not place real orders. For educational and informational purposes only, not financial advice. Always verify how the rope and bands behave on your specific symbol and timeframe before relying on them for live trading. Indikator
Thermometer OscillatorThermometer Oscillator
This one comes from David Bowden's Gann trading material — a quick way to check whether a trend still has gas in the tank or is about to stall. I built it as a simple momentum readout, nothing fancy.
Each bar gets scored on three things, added up into one number from -5 to +5:
1. Today's close vs. yesterday's close — +2 if higher, -2 if lower, 0 if it didn't move.
2. Today's close vs. today's open — same idea, +2/-2/0.
3. Today's range vs. yesterday's close — +1 if the whole bar sat above yesterday's close, -1 if it sat entirely below, 0 if yesterday's close landed inside the bar.
Add the three up and you get a number between -5 and +5. It plots like an RSI, with lines at +5, +3, 0, -3 and -5 so you can see where things stand at a glance. There's also a moving average on top (EMA by default, 9-period, but you can switch to SMA/WMA/RMA and change the length) to smooth out the noise.
Don't trade off this thing alone. It's an early-warning tool, not a signal. The way it's meant to be used: watch for it disagreeing with price. If a market's been sitting at +5 for a few days and then drops to +1 while price is still grinding out higher highs, that's momentum leaking out before the chart shows it.
Bowden's original write-up covers the daily version — previous day vs. current day. He does the same thing for the weekly trend, but you don't need a second calculation for that, just flip the chart to a weekly timeframe and read it the same way.
Educational tool only, not trading advice. Do your own homework before putting money behind it. Indikator
Minor H1 BIAS Analyse## 1. Purpose of the Script
The **Minor H1 BIAS Analyse** is designed to determine the short-term directional market BIAS.
It does not provide entries. Instead, it evaluates several trend, momentum, and structure conditions and classifies the market as:
Long
Short
Neutral
The script should therefore be used as a directional filter together with a separate entry strategy.
---
## 2. Structure of the Minor BIAS
The Minor BIAS is based on five components:
EMA Trend
Price vs EMA
Current Candle Direction
Previous H1 High / Low Break
Market Structure Break
Each bullish condition adds one point to the Bull Score.
Each bearish condition adds one point to the Bear Score.
The maximum possible score is:
5 Long
5 Short
---
## 3. EMA Trend
The script uses two exponential moving averages:
Fast EMA: 20
Slow EMA: 50
If the Fast EMA is above the Slow EMA:
+1 Long
If the Fast EMA is below the Slow EMA:
+1 Short
This represents the basic trend direction.
---
## 4. ATR Neutral Buffer
The script uses an optional ATR buffer around the EMAs.
Default settings:
ATR Length: 14
ATR Multiplier: 0.20
The buffer creates a neutral zone around the EMAs.
Price must move clearly above or below both EMAs before the condition becomes bullish or bearish.
This helps filter small movements and market noise.
---
## 5. Price vs EMA
For a bullish condition, price must close above both EMAs plus the ATR Buffer.
Result:
+1 Long
For a bearish condition, price must close below both EMAs minus the ATR Buffer.
Result:
+1 Short
If price remains inside the buffer area:
No Score
The dashboard displays:
Inside Buffer
---
## 6. Current Candle Direction
The script also evaluates the current candle.
Bullish Candle:
Close above Open
+1 Long
Bearish Candle:
Close below Open
+1 Short
Doji:
No Score
This adds a simple momentum component to the BIAS.
---
## 7. Previous H1 High / Low Break
The script checks whether price closes above or below the previous candle.
Close above Previous High:
+1 Long
Close below Previous Low:
+1 Short
No Break:
No Score
This filter can be enabled or disabled in the settings.
The script uses the candle close, not only the wick.
---
## 8. Market Structure
The script also analyzes the previous market structure.
Default Lookback:
5 candles
It calculates:
Structure High
Structure Low
If price closes above the Structure High:
Bullish Structure Break
+1 Long
If price closes below the Structure Low:
Bearish Structure Break
+1 Short
If neither level is broken:
Range
No Score
---
## 9. Score System
The final Minor BIAS is calculated from the Bull Score and Bear Score.
Possible Long points:
EMA Trend
Price vs EMA
Bullish Candle
Previous High Break
Bullish Structure Break
Possible Short points:
EMA Trend
Price vs EMA
Bearish Candle
Previous Low Break
Bearish Structure Break
A minimum of three points is required.
---
## 10. Minor LONG
The Minor BIAS becomes Long when:
Bull Score is at least 3
and
Bull Score is greater than Bear Score.
Example:
Bull Score: 4
Bear Score: 1
Result:
MINOR LONG
---
## 11. Minor SHORT
The Minor BIAS becomes Short when:
Bear Score is at least 3
and
Bear Score is greater than Bull Score.
Example:
Bull Score: 1
Bear Score: 4
Result:
MINOR SHORT
---
## 12. Neutral
If neither side reaches the required conditions, the BIAS remains Neutral.
Example:
Bull Score: 2
Bear Score: 2
Result:
NEUTRAL
Neutral therefore represents an unclear or mixed market situation.
---
## 13. Dashboard
The dashboard shows the current state of every component.
It contains:
BIAS
EMA Trend
Price vs EMA
H1 Candle
Previous H1 Break
Structure
ATR Buffer
It also displays the current:
Bull Score / Bear Score
Example:
4 / 1
This makes it possible to understand why the current BIAS is Long, Short, or Neutral.
---
## 14. Chart Visualization
The script can display:
Fast EMA
Slow EMA
Previous H1 High / Low
Structure High / Low
BIAS Background
BIAS Label
Dashboard
Each visualization can be enabled or disabled individually.
The calculations continue to work even when the corresponding chart elements are hidden.
---
## 15. Alerts
The script includes alerts for:
Minor H1 LONG
Minor H1 SHORT
Minor H1 NEUTRAL
These can be used to receive a TradingView notification when the directional BIAS changes.
---
## 16. Meaning for Trading
The Minor BIAS should not be treated as an entry signal.
A simple trading rule would be:
**MINOR LONG:** Prefer Long setups.
**MINOR SHORT:** Prefer Short setups.
**NEUTRAL:** Wait for clearer conditions.
The actual entry should come from a separate trading setup.
---
## 17. BIAS Strength
The score can also be used to estimate the strength of the current direction.
3 Points:
Valid directional confirmation
4 Points:
Strong confirmation
5 Points:
Very strong alignment
For example:
5 / 0 Long
represents stronger bullish confirmation than:
3 / 2 Long
even though both are classified as MINOR LONG.
---
## 18. Important Timeframe Note
The current script uses the timeframe of the active chart.
That means the calculations are only truly based on H1 when the indicator is used on a **1-hour chart**.
If the script is placed on M5 or M1, the calculations also use M5 or M1 data.
For a true H1 BIAS that remains identical on every chart, the calculations would need to use fixed 60-minute data.
---
## 19. Conclusion
The **Minor H1 BIAS Analyse** is a score-based directional filter.
It combines:
Trend
Price Position
Momentum
Previous Candle Break
Market Structure
At least three confirmations are required for a directional BIAS.
The final result is:
MINOR LONG
MINOR SHORT
NEUTRAL
Its purpose is to identify the stronger short-term market direction before a separate entry setup is considered.
++ This was only used on NQ ++
Indikator
Squeeze Pro [StrixEDGE]📊 WHAT IT DOES
StrixEDGE Squeeze Pro detects when Bollinger Bands contract inside Keltner Channels — a condition known as the "squeeze" — indicating extremely low volatility that typically precedes explosive moves. It measures squeeze intensity across three levels and uses MACD momentum to predict the breakout direction.
🔬 WHY IT'S DIFFERENT
Standard squeeze indicators show only ON/OFF. This version introduces three intensity levels: the tighter the Bollinger Bands compress inside Keltner Channels, the more powerful the expected breakout. Level 3 (extreme) squeezes historically produce the largest moves. Additionally, a real-time statistics table shows squeeze frequency, average duration, directional bias, and average post-squeeze move size for the current chart.
⚙️ HOW IT WORKS
The indicator calculates Bollinger Band width relative to Keltner Channel width. When BB fits inside KC, a squeeze is active. The ratio between their widths determines intensity:
• Level 1 (yellow dots): Light compression, ratio 0.8-1.0
• Level 2 (orange dots): Medium compression, ratio 0.5-0.8
• Level 3 (red dots): Extreme compression, ratio below 0.5
A four-color MACD momentum histogram shows breakout direction:
• Dark green = bullish accelerating, Light green = bullish fading
• Light red = bearish fading, Dark red = bearish accelerating
📈 HOW TO USE
• Wait for red/orange squeeze dots (Level 2-3) to accumulate
• When dots turn green (squeeze fires), enter in the histogram's direction
• Dark green histogram bars after squeeze = LONG entry
• Dark red histogram bars after squeeze = SHORT entry
• Level 3 squeezes produce the most reliable and powerful breakouts
• Use the stats table to understand squeeze behavior on your specific chart/timeframe
🎛️ INPUTS & DEFAULTS
BB: 20 period, 2.0 multiplier | KC: 20 period, 1.5 multiplier
MACD: 12/26/9 | Stats Lookback: 200 bars
All fully customizable.
═══════════════════════════════════════════════════════
🔧 CUSTOMIZATION
All parameters are fully adjustable through the indicator settings panel. Inputs are grouped logically:
• ⚙️ Core Parameters — main calculation settings
• 📊 Table Settings — table size (Tiny to Huge), position (4 corners), visibility toggle
• 🎨 Visual Settings — colors, show/hide elements
• 🔔 Alert Settings — threshold values for notifications
📊 DATA TABLE
A built-in data table displays all key metrics in real-time. Adjust the table size from Tiny to Huge to match your chart layout. Position it in any corner. Toggle visibility on/off.
🔔 ALERTS
Pre-built alert conditions for all major signals. Set up alerts via TradingView's alert dialog — select this indicator and choose from the available conditions.
⏱️ RECOMMENDED TIMEFRAMES
Works on all timeframes. Recommended: 1H, 4H, Daily for best signal quality. Lower timeframes produce more signals but with higher noise. Weekly/Monthly for position trading context.
✅ COMPLIANCE
• No repainting — all signals based on confirmed bar close data
• No future data references
• Open-source code — verify the logic yourself
⚠️ DISCLAIMER
This indicator is a technical analysis tool, not financial advice. It does not predict future price movements. Past patterns and signals do not guarantee future results. Trading involves substantial risk of loss. Always use proper risk management, including stop losses and appropriate position sizing. Never risk more than you can afford to lose. Indikator
Percentile Momentum Rotation [Pineify]Percentile Momentum Rotation
Overview
Percentile Momentum Rotation is a Pine Script v6 oscillator that converts fast, medium, and slow rate of change into a comparable spectrum. It shows a centered score, horizon coherence, a fast-slow wave, and a dashboard for momentum context rather than prediction.
Problem Definition
Raw ROC is a percentage return over one window. An 8-bar ROC has a different range from a 55-bar ROC, and the same value can be ordinary in a volatile regime but unusual in a quiet one. Averaging raw readings lets the largest horizon dominate, while fixed thresholds change meaning with the distribution. The design must retain each horizon's information but remove its local scale before combination.
Design Rationale
Each ROC is ranked against its own history and centered from -100 to +100, avoiding an assumption of normal returns. A z-score was rejected because outliers can distort its mean and deviation; a raw blend was rejected because it keeps the scale mismatch. The centroid is discounted when horizon polarities disagree or ranks spread apart. This favors coherent states but reacts less to an early one-window turn. The visual hierarchy follows these variables: primary score first, explanatory layers second.
Key Features
Three independently normalized ROC percentile streams.
A coherence-weighted composite and fast-slow rotation wave.
A state-colored spectrum, horizon fan, confirmed alerts, and dashboard.
Balanced, fast-focus, and slow-focus weighting.
How It Works
The script calculates percentage ROC over fast, medium, and slow lengths. ta.percentrank compares each current ROC with its configured history. Percentile 50 maps to zero, 100 to +100, and 0 to -100. Positive therefore means high versus that horizon's recent distribution; it does not guarantee a positive raw return.
The centered ranks form a weighted centroid; the three profiles shift emphasis across horizons. Polarity checks whether ranks share a side outside the dead zone, while compactness measures dispersion. Their 0-to-1 coherence controls a 0.55-to-1.00 consistency factor applied to the score.
The wave is half the fast-minus-slow rank difference. Color encodes score direction, halo intensity encodes coherence, and fan width shows dispersion. Output remains empty through warm-up. Visuals update intrabar; diamonds and alerts require bar close.
How Multiple Indicators Work Together
This is one pipeline, not a mashup. ROC supplies horizon change; percentile rank removes local scale; the centroid summarizes location; polarity and dispersion test coherence; and the consistency factor forms the score. The wave exposes lead-lag behavior that the centroid hides, while the fan visualizes disagreement. Removing a stage either removes momentum, restores the comparability problem, or hides confidence.
Trading Ideas and Insights
Upper and lower states organize review of relative momentum expansion. Synchronization means all horizons are unusual versus their own histories, not that a trade must follow. The wave reveals whether fast momentum leads or lags the slow horizon; repeated zero crossings describe unstable context. Confirm with independent structure and risk controls.
Unique Aspects
ROC and percentile rank are standard; the contribution is their information architecture. Each horizon is normalized against itself, then the composite is discounted by both side agreement and compactness. It separates historical location, synchronization, and lead-lag rotation; the same variables control halo, fan, and wave. No retrieved code is reproduced.
How to Use
Allow the slow ROC plus percentile history to warm up.
Start with Balanced and read score, coherence, and wave together.
Treat synchronization as context, then assess price structure and risk separately.
Use confirmed alerts; current-bar plots may move before close.
Disable secondary layers for a cleaner chart.
Customization
Short ROC windows react faster but rotate more often; long windows add persistence and lag. Longer percentile history provides broader context but adapts more slowly after regime shifts. The dead zone sets how much near-median movement is directionless. Rotation thresholds define context and extremes; Synchronization Threshold sets required agreement. Weight profiles change the analytical question, so comparisons should keep settings consistent.
Assumptions and Limitations
The source and available history must be representative enough for ranking. Percentiles are relative: a high rank can occur while raw returns are negative if the decline is milder than recent declines. Results depend on lengths, lookback, and structural breaks. It is lagging and omits volume, execution, fundamentals, and structure. Visuals can change before close; alerts wait for confirmation. No future values or external data are used, but this does not establish performance.
Conclusion
Percentile Momentum Rotation turns incompatible ROC scales into an auditable spectrum. It keeps relative location, coherence, and lead-lag rotation distinct but connected, helping diagnose momentum context without treating thresholds as guaranteed entries.
Indikator
Triple Supertrend Confluence [MarkitTick]💡 A triple-layer Supertrend confluence system that fuses adaptive volatility bands, multi-timeframe bias, momentum strength, volume conviction, and a cooldown throttle into a single, high-confidence trend signal — then automates the entire trade plan around it with ATR-scaled stop-loss and three staged take-profit levels.
✨ Originality and Utility
Most Supertrend implementations on the platform are single-instance: one ATR period, one multiplier, one line. This script restructures the classic Supertrend into a voting system. Three independently parameterized Supertrend instances (a primary "core" trend and two auxiliary "fast" and "slow" trackers) are calculated in parallel from the same underlying price source, and a signal is only treated as valid when a configurable number of these instances agree on direction. This confluence layer is what separates the tool from a standard Supertrend plot — it is designed to filter out the single biggest weakness of trend-following overlays: getting whipsawed by a solitary indicator flipping on marginal price action.
On top of the consensus layer, the script lets traders stack up to four independent, optional confirmation filters (trend strength via ADX/DMI, higher-timeframe directional bias, relative volume, and a bar-count cooldown) before a signal is considered "confirmed." Each filter can be toggled independently, so the tool scales from a bare-bones single Supertrend up to a fully gated, multi-condition trend-following system. A real-time dashboard keeps every filter's pass/fail state visible at a glance, and an automated trade-planning layer converts each confirmed flip into a structured entry/stop/three-tier-target plan, plotted directly on the chart and exposed through webhook-ready JSON alert payloads.
🔬 Methodology and Concepts
• Core Supertrend Engine
The underlying trend engine follows the standard Supertrend construction: an ATR-derived envelope is built around a price source, with an upper band (source plus a multiple of ATR) and a lower band (source minus a multiple of ATR). These bands are "ratcheted" bar to bar — the lower band can only rise or reset if price closes below the prior lower band, and the upper band can only fall or reset if price closes above the prior upper band. The active trend line switches between the lower band (uptrend) and upper band (downtrend) whenever price closes through the opposite band, producing the familiar stepped Supertrend line. This engine is reused three times with different parameters to build the confluence system described below.
• Adaptive Source Smoothing
Rather than feeding raw HL2 price directly into the Supertrend engine, the script offers eight optional smoothing methods to pre-condition the source: Simple, Exponential, and Wilder's Moving Averages; a Double-Pass Weighted Moving Average; a Triple-Pass Volume-Weighted Moving Average; a Hull Moving Average; a custom slope-adjusted average (LLAMA) that blends a simple mean with a linear slope projection over the lookback window; and a single-state Kalman Filter that recursively updates an estimate and its error covariance bar by bar to produce a noise-adaptive average. Smoothing the source before it reaches the Supertrend calculation reduces false flips caused by single-bar noise spikes, at the cost of some responsiveness.
• Adaptive Volatility Factor
Instead of using a fixed ATR multiplier for the core Supertrend band width, the script can compute a percentile rank of current ATR against its own recent history (a lookback window of your choosing). This rank is then mapped linearly onto a user-defined minimum/maximum multiplier range. In practice, this means the band automatically widens during historically high-volatility regimes (reducing whipsaw) and tightens during historically low-volatility regimes (increasing sensitivity), rather than using one static multiplier across all conditions.
• Triple Consensus Voting
Two additional Supertrend instances — a faster-reacting pair (shorter ATR length, smaller multiplier) and a slower-reacting pair (longer ATR length, larger multiplier) — run alongside the core engine on the same smoothed source. When consensus mode is enabled, a signal is only marked confirmed if at least two of the three instances (including the core) agree on direction. This is a simple majority-vote filter designed to suppress signals that are specific to one particular band setting rather than representative of the broader trend structure.
• ADX / DMI Trend Strength Filter
An optional Average Directional Index filter, calculated using Wilder's Directional Movement methodology, requires ADX to be at or above a user-defined threshold before a flip is confirmed. This is a standard technique for distinguishing genuine directional moves from choppy, non-trending price action, since Supertrend-style systems are known to underperform in low-ADX ranging conditions.
• Higher-Timeframe Bias Filter
An optional filter pulls the trend direction of the same Supertrend engine calculated on a higher, user-selected timeframe, and only confirms a signal if it aligns with that higher-timeframe bias. The higher-timeframe value is read from the prior, fully closed bar on that timeframe to avoid any intra-bar recalculation, ensuring the filter reflects only confirmed historical structure rather than an in-progress bar.
• Volume Confirmation Filter
An optional filter compares current bar volume against its own moving average, requiring volume to exceed the average by a user-defined multiple before a signal is confirmed. This is a simple conviction check: trend changes accompanied by above-average participation are treated as more reliable than those occurring on thin volume.
• Cooldown Guard
An optional bar-count throttle prevents a new confirmed signal in the same direction as a recent prior signal if too few bars have elapsed since that prior signal within the same directional segment, reducing rapid re-signaling during choppy transition periods.
• Confirmation Lag Notice
All confirmation logic (consensus vote, ADX filter, HTF bias, volume filter, cooldown guard) and the resulting BULL/BEAR labels, alerts, and trade-level plotting are evaluated strictly on confirmed, closed bars using barstate.isconfirmed. This means every signal displayed or alerted is final and will not repaint once printed. However, users should be aware that a signal is only confirmed one bar after the actual Supertrend flip occurs, since the confirmation checks (particularly the higher-timeframe bias filter) require a fully closed bar to evaluate safely. This introduces a small, deliberate one-bar lag between the raw trend flip and the confirmed signal in exchange for eliminating repainting.
• Automated Trade Level Engine
On every confirmed flip, the script calculates a full trade plan from the entry price (the confirmed close), an ATR-scaled stop-loss (a user-defined multiple of ATR away from entry), and three take-profit levels defined as user-configurable risk:reward multiples of the initial stop distance. These levels are drawn as extending lines and labels, with shaded risk and reward zones between them, and refresh automatically on each new confirmed signal unless the signal is manually locked.
🎨 Visual Guide
Stepped trend line (color reflects the Up/Down Color inputs): traces the active Supertrend band. It plots along the lower band while price is in an uptrend and the upper band while price is in a downtrend.
Muted/gray trend line: when a filter is active but not yet satisfied, the trend line temporarily switches to the Unconfirmed Color to signal that the raw trend has flipped but confirmation is still pending.
Soft background fill (Up Fill / Down Fill colors): a translucent shaded region behind price reinforcing the current trend direction.
Heatmap candles: when enabled, candle bodies and wicks are recolored using the Heatmap Up/Down colors to match the current trend direction, offering an at-a-glance visual of trend state independent of the line itself.
"BULL" / "BEAR" labels: printed below or above the bar respectively, only on confirmed flips that pass every active filter.
Gray cooldown background: a shaded band that appears across the chart while the Cooldown Guard is actively suppressing new signals.
Trade level lines: a solid red Stop-Loss line, a dashed blue Entry line, and three dashed teal Take-Profit lines (TP1 lightest, TP3 most opaque), each extending to the right of the current bar with a price label attached, shown only when Show Trade Levels is enabled.
Shaded risk/reward zones: a light red fill between Stop-Loss and Entry (the risk zone) and a light teal fill between Entry and TP3 (the reward zone).
On-chart dashboard table: displays symbol/timeframe, Lock status, current Trend direction, Confirmed state, ADX value with a color-coded strength percentage, active Adaptive Filter type, Consensus vote count, HTF Bias direction and pass/fail, Volume filter pass/fail, and remaining Cooldown bars — all updating on the most recent bar.
📖 How to Use
Use the stepped trend line and background fill as the primary trend read: price above the line with an up-colored fill suggests an uptrend context; price below with a down-colored fill suggests a downtrend context.
Treat a "BULL" or "BEAR" label as the actionable signal rather than the raw line flip — labels only appear once every enabled filter has passed, meaning the signal has already been screened for trend strength, higher-timeframe alignment, volume conviction, and cooldown status.
If the trend line is showing the Unconfirmed Color, the underlying trend has technically flipped but is still waiting on one or more active filters — treat this as a "watch" state rather than a trade trigger.
Check the dashboard on each new bar to see exactly which filter(s) are passing or failing before a signal can confirm; this is useful for understanding why an expected signal did not appear.
When Show Trade Levels is enabled, use the plotted Stop-Loss, Entry, and TP1/TP2/TP3 lines as a starting reference for structuring a trade around a confirmed signal — adjust position sizing and targets to your own risk tolerance.
Enable Lock Signal to freeze the current trade-level plot in place (useful for screenshots or reviewing a specific setup) without it being overwritten by a new signal.
The JSON alert payloads are formatted for direct use in webhook-based automation, carrying action, ticker, timeframe, direction, and price fields for long entries, short entries, and their corresponding close-position triggers.
⚙️ Inputs and Settings
ATR Len / Factor: the ATR lookback and multiplier for the core Supertrend engine; higher Factor values produce a looser band and fewer, larger-magnitude signals.
Adaptive Factor (and Min/Max/Rank Len): when enabled, replaces the fixed Factor with a volatility-percentile-driven multiplier that ranges between Factor Min and Factor Max based on where current ATR sits within its own recent history.
Use ADX Filter / ADX Threshold / ADX Length: gates signal confirmation on trend strength; raise the threshold to demand stronger directional conviction before confirming.
Adaptive Filter / Adaptive Filter Len: selects the source-smoothing method applied before the Supertrend calculation, and its lookback length.
Use HTF Confluence / HTF: requires the selected higher timeframe's own Supertrend direction to agree before confirming a signal.
Use Volume Filter / Volume Avg Len / Volume Mult: requires current volume to exceed its moving average by the given multiple before confirming.
Use Cooldown Guard / Cooldown Bars: suppresses new same-direction signals for a set number of bars following a recent prior signal in the same directional segment.
Use Triple Consensus / Fast Factor / Fast ATR Len / Slow Factor / Slow ATR Len: enables the majority-vote filter and configures the auxiliary fast and slow Supertrend instances used to build consensus.
Lock Signal: freezes the currently plotted trade levels, preventing them from updating on a new signal.
Show Trade Levels: toggles the automated Entry/SL/TP1-3 line and label plotting.
SL ATR Mult: the ATR multiple used to place the stop-loss distance from entry.
TP1/TP2/TP3 R:R: the risk:reward multiples used to place each take-profit level relative to the stop distance.
Heatmap Candles / BULL-BEAR Labels / Show Dashboard / Position: visual display toggles and dashboard placement.
Long/Short/Close Long/Close Short Action: customizable string values embedded in the JSON alert payload's "action" field, for mapping to specific webhook automation commands.
🔍 Deconstruction of the Underlying Scientific and Academic Framework
• Volatility-Based Trend Following (Supertrend / ATR Envelopes)
The core engine descends from the broader family of volatility-adjusted trend-following bands, which use Average True Range (a measure of typical price movement magnitude popularized by J. Welles Wilder) to scale a trailing stop-and-reverse line to prevailing market volatility rather than a fixed price distance. The ratcheting band logic ensures the line never moves against the prevailing trend, which is the defining mechanical property of a trailing-stop-style trend system as opposed to a simple moving average crossover.
• Percentile Ranking for Regime Adaptation
The adaptive factor mechanism applies percentile rank normalization — expressing current ATR as its standing relative to a distribution of its own recent historical values — as a way of contextualizing volatility without relying on a fixed absolute threshold, which allows the same logic to be meaningfully applied across instruments and timeframes with very different baseline volatility levels.
• Ensemble / Majority-Vote Filtering
The Triple Consensus mechanism is a straightforward application of ensemble logic: combining multiple independent estimators (in this case, differently parameterized instances of the same underlying model) and requiring agreement among a majority before acting. This is a well-established technique for variance reduction in signal processing and forecasting contexts, on the premise that independent estimators are less likely to agree by chance during noise-driven, non-trending conditions than during genuine directional moves.
• Wilder's Directional Movement / ADX
The ADX filter is drawn directly from J. Welles Wilder's Directional Movement System, which decomposes price movement into positive and negative directional components and derives a smoothed index (ADX) representing trend strength independent of direction. ADX below common threshold levels is widely associated with range-bound, non-trending conditions in technical analysis literature.
• Recursive State Estimation (Kalman Filtering)
The optional Kalman Filter smoothing method applies a simplified single-state form of the Kalman recursive estimation framework from control theory and signal processing, in which a running estimate is continuously updated by weighting new observations against the estimate's own error covariance, producing a smoothing average that adapts its responsiveness based on recent prediction error rather than using a fixed lookback window.
• Slope-Adjusted Trend Extrapolation (LLAMA)
The LLAMA smoothing option combines a simple arithmetic mean with a linear slope term derived from the change in price over the lookback window, projecting the average forward along the recent trend direction — a lightweight application of linear extrapolation principles used to reduce the inherent lag of simple averaging methods.
• Volume as a Conviction Proxy
The volume filter reflects the broader technical-analysis principle that price movements accompanied by above-average participation carry more informational weight than those on thin volume, a concept with roots in classical volume-price analysis dating back to early technical analysis literature (e.g., Dow Theory's treatment of volume as a confirming factor).
⚠️ Disclaimer
All provided scripts and indicators are strictly for educational exploration and must not be interpreted as financial advice or a recommendation to execute trades. We expressly disclaim all liability for any financial losses or damages that may result, directly or indirectly, from the reliance on or application of these tools. Market participation carries inherent risk where past performance never guarantees future returns, leaving all investment decisions and due diligence solely at your own discretion. Indikator
Nonparametric Relative Momentum [BackQuant]Nonparametric Relative Momentum
Overview
Nonparametric Relative Momentum is a percentile-rank oscillator that measures where the current price or momentum observation sits relative to its own recent empirical history.
Unlike conventional momentum oscillators that transform price using fixed arithmetic relationships, this indicator uses rank statistics . The current observation is compared directly against the previous values in a rolling window and converted into a percentile score from 0 to 100.
The result answers a simple question:
How extreme is the current observation relative to what this market has actually done recently?
Two calculation modes are available:
Price ranks the selected price source directly.
Momentum first measures price change across a configurable horizon, then ranks that momentum against its own recent history.
The oscillator also includes:
Mid-rank handling for tied observations.
Optional output smoothing.
An EMA signal line.
Configurable overbought and oversold zones.
Stepped intensity colouring as the rank becomes more extreme.
Main-chart candle colouring from the 50 midline regime.
Alerts for midline, extreme-zone and signal-line crossings.
Why “nonparametric”?
In statistics, a parametric method generally assumes that data can be described by a particular distribution or by parameters associated with that distribution.
A nonparametric method does not require the same distributional assumption.
Percentile ranks are a classic example.
The oscillator does not need to assume that recent price changes are:
Normally distributed.
Symmetric.
Constant in volatility.
Characterised by a stable mean and standard deviation.
Instead, it works directly from the ordering of the observed data.
If the current momentum observation is greater than almost every momentum observation in the recent window, it receives a high rank.
If it is lower than almost everything observed recently, it receives a low rank.
This makes the oscillator fundamentally relative to the market’s own recent empirical distribution.
Core calculation
The calculation occurs in three stages:
Select the series to rank.
Calculate its empirical percentile rank.
Optionally smooth that rank and calculate a signal average.
The selected ranking target depends on the Rank Target input.
Price Mode
In Price mode:
Target = Selected Price Source
The current source value is compared with the previous values in the Rank Window.
This answers:
Where is current price positioned within its recent price distribution?
A value near 100 means current price is above almost every observation in the comparison window.
A value near 0 means it is below almost every observation.
A value near 50 means it sits near the middle of its recent distribution.
Because Price mode ranks the price level itself, it behaves somewhat like a stochastic or price-position oscillator, although the calculation is based on empirical ranking rather than highest-lowest range normalisation.
Momentum Mode
Momentum mode first calculates:
Momentum = Source - Source
This measures the absolute price change across the selected Momentum Length.
The resulting momentum series is then percentile-ranked over the Rank Window.
The oscillator therefore answers:
How strong is the current momentum observation compared with recent momentum observations?
This is different from asking whether price itself is historically high or low.
For example, price can be near a recent high while momentum has weakened considerably. In that situation:
Price mode may remain highly ranked.
Momentum mode may fall toward the centre or lower half of the distribution.
Conversely, price does not need to be at a long-term extreme for momentum to rank very highly if the current change is unusually strong relative to recent movements.
Why Momentum mode is different from traditional RSI
The standard Relative Strength Index developed by J. Welles Wilder compares smoothed positive and negative price changes.
Its calculation depends on the relative magnitude of average gains and average losses.
Nonparametric Relative Momentum does not use that formula.
Instead:
A momentum observation is calculated.
That observation is ranked against its own historical sample.
For this reason, Momentum mode can be thought of as a rank-based relative momentum oscillator .
Both traditional RSI and this oscillator are bounded between 0 and 100, but the meaning of those values is different.
For example:
RSI = 90
means the balance of smoothed gains versus losses has produced an RSI reading of 90.
Nonparametric Relative Momentum = 90
means the current momentum observation ranks around the upper end of its recent empirical momentum distribution.
That distinction is important.
Percentile rank calculation
For each bar, the indicator compares the current target with every observation in the preceding Rank Window.
It counts:
How many previous values are below the current value.
How many previous values are exactly equal to it.
The percentile rank is then:
Rank = 100 × (Values Below + 0.5 × Equal Values) / Window Length
This produces an oscillator between 0 and 100.
Why use rank instead of magnitude?
Consider two markets.
Market A may normally move only 0.5% over the selected momentum horizon.
Market B may routinely move 5%.
A raw momentum threshold cannot be interpreted the same way for both.
Ranking changes the question.
Instead of asking:
How many points or percent did this market move?
the oscillator asks:
How unusual is this move relative to this market’s own recent behaviour?
This allows the same 0–100 framework to adapt naturally to different price scales and volatility regimes.
Mid-rank treatment of ties
A simple percentile implementation might count only observations strictly below the current value.
That can distort the result when repeated values occur.
This indicator uses mid-rank treatment .
If historical observations equal the current value, each tie contributes one half rather than being classified entirely above or below.
For example, suppose:
40% of observations are below the current value.
20% are exactly equal.
40% are above.
The mid-rank result is:
40 + 0.5 × 20 = 50
This places the tied observation at the centre of its equal-value group.
Mid-ranks are commonly used in rank-based statistics because they provide a more balanced treatment of ties.
Rank Window
The Rank Window determines how much historical data defines the current empirical distribution.
A shorter Rank Window:
Adapts quickly.
Responds strongly to recent regime changes.
Produces more rapid movement between percentiles.
Can create noisier extreme readings.
A longer Rank Window:
Builds the ranking from a larger sample.
Produces a more stable percentile estimate.
Makes extremes harder to reach.
Responds more slowly when market behaviour changes.
The window therefore controls the memory of the oscillator.
It does not smooth the underlying target directly. It changes the reference distribution against which the target is ranked.
Momentum Length
Momentum Length is used only when Rank Target is set to Momentum.
It controls the horizon over which price change is measured:
Momentum = Current Source - Source from Momentum Length bars ago
Shorter values:
Measure faster momentum.
React to shorter impulses.
Change direction more frequently.
Longer values:
Measure broader displacement.
Focus on more persistent movement.
Ignore more short-term fluctuation.
The Momentum Length and Rank Window perform separate roles.
Momentum Length determines what movement is measured.
Rank Window determines the historical sample against which that movement is judged.
Output Smoothing
The raw percentile rank can optionally be passed through an EMA.
A value of 1 leaves the rank effectively unsmoothed.
Higher values:
Reduce rapid rank fluctuations.
Create a smoother oscillator.
Reduce short-lived extreme readings.
Introduce additional lag.
The smoothing occurs after the percentile calculation.
It does not change how observations are ranked.
The 50 midline
The oscillator is centred around 50.
A value above 50 means the current observation ranks above the midpoint of its recent distribution.
A value below 50 means it ranks below the midpoint.
The interpretation depends on the selected mode.
Price mode above 50
Current price is positioned in the upper half of its recent price distribution.
Price mode below 50
Current price is positioned in the lower half.
Momentum mode above 50
Current momentum is stronger than roughly the middle of its recent momentum observations.
Momentum mode below 50
Current momentum is weaker relative to its recent distribution.
The indicator also uses this midline to colour main-chart candles:
Above or equal to 50 = bullish colour.
Below 50 = bearish colour.
This provides a simple relative-regime view on the price chart.
Percentile extremes
Because the oscillator represents rank rather than an unbounded magnitude, readings near 0 and 100 carry a straightforward interpretation.
Near 100
The current observation is greater than almost every value in the recent comparison window.
Near 0
The current observation is lower than almost every value.
These are empirical extremes.
They do not mean price or momentum cannot become more extreme.
A value near 100 can persist while a strong trend continues because new observations may repeatedly remain near the top of the evolving distribution.
Likewise, readings near 0 can persist during sustained downside momentum.
Overbought and Oversold zones
The default static zones are:
Overbought: 90–100
Oversold: 0–10
These are configurable.
The labels “overbought” and “oversold” describe statistical location, not guaranteed reversal conditions.
An overbought reading means:
The ranked observation is near the top of its recent empirical distribution.
An oversold reading means:
It is near the bottom.
During a range, these areas may help identify local extremes.
During a persistent trend, the oscillator can remain in an extreme zone for extended periods.
The zones should therefore be interpreted together with:
Trend context.
Price structure.
Oscillator direction.
Signal-line behaviour.
Why 90/10 instead of 70/30?
Traditional RSI commonly uses 70 and 30.
That convention does not need to apply to a percentile-rank oscillator.
A rank above 90 means the current observation is in approximately the upper tail of the recent empirical sample, while a reading below 10 represents the lower tail.
Using more extreme default zones makes them intentionally selective.
Users who want broader zones can move the boundaries toward values such as 80 and 20.
Signal line
The white Moving Average line is an EMA of the final oscillator:
Signal = EMA(Percentile Rank Oscillator, Signal Length)
This provides a slower reference against which short-term rank movement can be compared.
Oscillator above signal
The percentile rank is strengthening relative to its own recent smoothed level.
Oscillator below signal
The rank is weakening.
Crossovers can be used to identify changes in short-term momentum within the broader percentile regime.
For example:
A bullish crossover below the oversold zone can indicate rank beginning to recover from an extreme.
A bearish crossover above the overbought zone can indicate deterioration from an upper-tail reading.
A crossover near 50 may represent a more neutral momentum transition.
Signal crosses should not be interpreted independently from oscillator location.
Stepped oscillator colouring
The oscillator uses stepped colour intensity based on its position relative to the 50 midline.
Above 50, colours progressively strengthen as the percentile reaches higher levels.
Below 50, bearish intensity progressively strengthens as the percentile falls.
The main regions are approximately:
50–62.5: modest positive rank.
62.5–75: strengthening positive rank.
75–90: strong positive rank.
90–99: upper-tail extreme.
99–100: exceptional upper-tail rank.
The lower half mirrors this concept:
37.5–50: modest negative rank.
25–37.5: weakening relative state.
10–25: strong negative rank.
1–10: lower-tail extreme.
0–1: exceptional lower-tail rank.
These colours do not introduce additional calculations or signals.
They visually communicate how far the oscillator has moved into its empirical distribution.
Column presentation
The percentile oscillator is plotted as columns around a histogram base of 50.
This means:
Values above 50 extend upward.
Values below 50 extend downward from the midline.
Although the numerical scale remains 0–100, this presentation visually emphasises deviation from the centre of the distribution.
The 50 level therefore functions as the oscillator’s equilibrium reference.
Price mode versus Momentum mode
The two modes answer different questions and should not be treated interchangeably.
Price Mode
Asks:
Where is price relative to its recent distribution?
This makes it useful for:
Range position.
Breakout context.
Relative price extremes.
Stochastic-like analysis.
Momentum Mode
Asks:
Where is current price change relative to the recent distribution of price changes?
This makes it useful for:
Momentum expansion.
Momentum exhaustion.
Relative impulse analysis.
Trend-strength transitions.
Momentum mode can identify weakening momentum before price itself leaves the upper part of its distribution.
Price mode can remain elevated simply because the market is still trading near recent highs.
Example: strong uptrend
Suppose price has been rising steadily.
Price Mode may remain above 90 because current price continually sits near the upper edge of its recent range.
Momentum Mode may behave differently:
It can rise toward 100 during acceleration.
Fall back toward 50 when the trend continues at a more ordinary pace.
Drop below 50 if momentum deteriorates significantly even while price remains relatively high.
This distinction can help separate price location from momentum condition .
Example: volatility regime change
Suppose a market normally changes by only small amounts, then suddenly produces a large directional move.
Raw momentum alone shows a large number.
The percentile rank provides additional context by showing whether that movement is unusual relative to the recent distribution.
If the current momentum is greater than nearly every recent observation, the oscillator moves toward 100.
If the market has already experienced many similarly large moves, the same absolute momentum may receive a much less extreme rank.
The indicator therefore adapts automatically to changing empirical behaviour without requiring fixed momentum thresholds.
Midline crossings
A crossover above 50 indicates the ranked series has moved into the upper half of its recent distribution.
A cross below 50 indicates movement into the lower half.
In Momentum mode, these crossings can be used as a simple relative momentum regime:
Above 50 = comparatively stronger momentum state.
Below 50 = comparatively weaker momentum state.
In Price mode, they indicate whether price is above or below the central portion of its recent rank distribution.
These crossings also control the optional main-chart candle colours.
Extreme-zone crossings
The indicator provides alerts when:
The oscillator crosses upward into the overbought zone.
The oscillator crosses downward into the oversold zone.
These alerts identify entry into an extreme percentile area.
They do not indicate that the extreme has ended.
For reversal-oriented analysis, a trader may instead monitor:
A subsequent exit from the zone.
A signal-line crossover.
Divergence with price.
A break in market structure.
Divergence interpretation
Because Momentum mode ranks momentum rather than price, it can also be useful for examining momentum divergence.
For example:
Price may make a higher high while the oscillator produces a lower percentile peak.
This indicates that the latest momentum observation is less exceptional relative to its recent history than it was during the previous price high.
The reverse can occur at lows.
As with conventional divergence, this is evidence of changing momentum characteristics, not confirmation that price must reverse.
How to use the indicator
1. Relative momentum regime
In Momentum mode, use the 50 midline as a simple regime reference:
Above 50 = positive relative momentum state.
Below 50 = negative relative momentum state.
2. Momentum extremes
Use the configurable zones to identify unusually high or low momentum ranks.
Rather than automatically fading these conditions, determine whether the market is:
Trending.
Exhausting.
Breaking out.
Returning toward equilibrium.
3. Signal-line transitions
Oscillator and signal-line crosses can help identify shorter-term changes in rank direction.
The location of the crossover matters.
A bullish crossover at 5 carries different context from one at 95.
4. Price-distribution analysis
Switch to Price mode when the objective is to measure where the current market sits within its recent price distribution.
This can be useful for:
Breakout analysis.
Range positioning.
Relative high/low detection.
5. Trend confirmation
Momentum remaining consistently above 50 can support an existing bullish trend.
Momentum remaining below 50 can support a bearish trend.
Repeated oscillation around 50 indicates that relative momentum is changing sides frequently.
6. Candle regime colouring
The optional overlay candles make the oscillator’s midline state visible directly on the main price chart.
This can be useful when the oscillator pane is being used primarily for extremes and signal-line analysis.
Input guide
Rank Target
Selects what is percentile-ranked.
Price ranks the source itself.
Momentum ranks its change over the selected Momentum Length.
Rank Window
Controls the empirical comparison sample.
Longer values are smoother and statistically broader. Shorter values adapt more quickly.
Momentum Length
Controls the displacement horizon in Momentum mode.
It has no effect in Price mode.
Output Smoothing
Applies optional EMA smoothing to the percentile rank.
1 produces the raw rank.
Signal Length
Controls the EMA signal line.
Shorter values follow the oscillator more closely. Longer values produce slower crossover signals.
Overbought Zone
Sets the lower boundary of the upper extreme area.
Oversold Zone
Sets the upper boundary of the lower extreme area.
How this differs from RSI
Traditional RSI:
Separates gains and losses.
Smooths their magnitude.
Calculates a relative-strength ratio.
Transforms that ratio onto a 0–100 scale.
Nonparametric Relative Momentum:
Calculates price or momentum directly.
Ranks the current observation against historical observations.
Uses no gain/loss ratio.
Uses no assumed distribution.
The identical 0–100 scale therefore represents a different statistical concept.
How this differs from Stochastic
A conventional stochastic oscillator measures where current price lies between the highest high and lowest low of a window.
Its basic concept is:
(Current - Lowest) / (Highest - Lowest)
Nonparametric Price mode instead asks how many historical observations are below the current price.
This distinction matters because the rank considers the entire empirical ordering of the sample, not only its two extreme endpoints.
Two windows can have identical highs, lows and current price but different internal distributions.
A stochastic calculation can return the same value in both cases, while percentile rank can differ because the number of observations above and below the current price is different.
How this differs from a Z-score
A Z-score measures deviation from a mean in standard-deviation units:
Z = (Current Value - Mean) / Standard Deviation
That calculation depends directly on the sample mean and dispersion.
Percentile rank depends only on ordering.
As a result, an extreme outlier can heavily alter a mean and standard deviation but has much less influence on the ordering of the remaining observations.
This is one of the reasons rank statistics can be useful when financial data contains skew, fat tails or isolated extreme moves.
Strengths
Uses a nonparametric empirical ranking process.
Requires no assumption of normality.
Produces an intuitive bounded 0–100 scale.
Adapts naturally to the recent behaviour of each market.
Supports both price-location and momentum-ranking modes.
Uses mid-ranks for tied observations.
Normalises momentum extremes without relying on fixed point or percentage thresholds.
Includes configurable smoothing and signal analysis.
Provides direct midline regime colouring on the main chart.
Limitations
A percentile rank measures relative position, not absolute magnitude.
A reading of 100 does not indicate how much larger the current observation is than the rest of the sample.
Persistent trends can remain at extreme ranks for extended periods.
Short Rank Windows can generate rapid percentile changes.
Long Rank Windows adapt more slowly to regime shifts.
Momentum mode uses absolute source change rather than percentage return, although ranking substantially reduces scale dependence within a single instrument.
Extreme readings are not automatic reversal signals.
Signal-line crosses can whipsaw in noisy conditions.
The oscillator is reactive and does not forecast future price.
Alerts
The indicator provides alerts for:
Cross Up 50: oscillator enters the upper half of its distribution.
Cross Down 50: oscillator enters the lower half.
Overbought: oscillator crosses upward through the selected upper-zone boundary.
Oversold: oscillator crosses downward through the selected lower-zone boundary.
Bull: oscillator crosses above its signal EMA.
Bear: oscillator crosses below its signal EMA.
Summary
Nonparametric Relative Momentum converts either price or momentum into an empirical percentile rank.
Instead of asking how far an observation is from a moving average, how many standard deviations it sits from a mean, or what ratio of gains to losses produced it, the indicator asks where that observation ranks relative to its own recent history.
In Price mode, it measures the relative location of price within its historical distribution.
In Momentum mode, it first calculates price displacement across a chosen horizon and then measures how exceptional that momentum is relative to recent momentum observations.
A mid-rank procedure handles tied values, optional EMA smoothing controls visual responsiveness, and a separate signal average provides crossover analysis. The 50 midline separates the upper and lower halves of the empirical distribution, while configurable overbought and oversold zones highlight the tails.
The result is a distribution-free relative momentum framework that adapts to the observed behaviour of the market rather than relying on fixed magnitude thresholds or an assumed statistical distribution.
Indikator
Momentum PowerTrend & Momentum Power (Futures Traders)
What it does
This indicator gives NQ traders a fast read on trend and momentum strength — for NQ and ES side by side — without having to flip charts. It's built for spotting confluence: when NQ and ES are both showing strong trend/momentum in the same direction, that agreement is often more meaningful than either instrument alone. When they diverge, that relative strength/weakness between the two can be just as useful to watch.
How it works
Trend Power is derived from Wilder's DMI/ADX — it measures how strong a directional trend is, not just whether one exists.
Momentum Power is an ATR-normalized rate-of-change — it measures how fast price is moving relative to recent volatility, so readings stay consistent across different volatility regimes.
Each reading is scored 1–3 dots (weak/medium/strong) and colored bullish, bearish, or neutral/indecisive.
The dashboard shows four rows: NQ Trend, NQ Momentum, ES Trend, ES Momentum — so you can see both instruments' internal state at a glance.
ES data is pulled live via request.security, so no need to switch charts.
New: Candle coloring on confluence
When enough dots across all four rows agree on direction (default: 7 of 12), the candles on your chart change color — green for bullish consensus, red for bearish. This is a visual cue for when NQ and ES trend/momentum are aligned, not aligned individual instrument readings in isolation.
Important — this is not a buy/sell signal
This tool does not generate entries, exits, or trade recommendations. It's a read on relative trend and momentum strength between NQ and ES to help you gauge confluence and context. Candle coloring reflects dot agreement, not a system signal — it still requires your own judgment, risk management, and confirmation from your broader trade plan before acting on anything you see.
Inputs
ES symbol is configurable (defaults to CME_MINI:ES1!; swap for micros or a fixed contract month)
All thresholds (trend/momentum weak/medium/strong, deadzones) are adjustable per your own calibration
Dot consensus threshold and candle colors are configurable independently of the dashboard dot colors Indikator
Khabib Takedown Fractal Nest Breakdown ViprasolKhabib Takedown — Fractal Nest Breakdown 🤼
CONCEPT
This tool looks for SELF-SIMILARITY in a decline: a big bearish leg (lower high -> lower low)
with a smaller bearish leg nested inside it that is a scaled copy — same shape, a fraction of
the size. When the small "fractal" completes in the direction of the big one (a break of the
last low), the structure grounds price -> SHORT. It is a fractal-echo measurement, not a plain
lower-low. The nesting ratio between the small leg and the big leg is the core filter.
HOW IT DETECTS
- Swings are found with confirmed pivot highs/lows (left/right bar lookback) and chained into a
lightweight zigzag.
- The tool reads the last four alternating swings (high, low, high, low).
- Big leg = first high minus first low; small leg = second high minus second low.
- A valid nest requires: lower high and lower low (bearish structure); big leg >= (Min big x ATR);
small leg positive; and the nesting ratio (small/big) inside the band .
- The signal fires when price closes below the most recent swing low and the bar closes red.
- ATR (Wilder) scales the minimum big-leg size across instruments and timeframes.
ENTRY / STOP / TARGET
- Entry: SHORT on the close of the confirming (red) bar that breaks the last low.
- Stop: above the second (inner) swing high plus an ATR buffer (default 0.3 x ATR).
- Target: entry minus R multiple x risk (default 2R, where risk = stop distance).
- The script draws the big leg and the nested small leg, plus filled TP and SL zones that extend
to the right until price touches one of them.
NON-REPAINTING
Pivots are only used once fully confirmed (they require the right-side bars), and the signal is
evaluated on bar close (barstate.isconfirmed). Drawings are created on the confirmed bar. The tool
does not repaint completed signals. Live, the forming bar can still change until it closes, as with
any bar-close tool.
FEATURES
- Fractal nesting (scaled self-similar legs), not a plain lower-low break.
- ATR-scaled minimum big-leg requirement and adjustable nesting-ratio band.
- Automatic R-multiple TP and ATR-buffered SL, drawn as zones that extend until hit.
- One-trade-at-a-time option and a minimum-bars-between-signals gap to reduce clustering.
- On-chart status table (open trades) and an alertcondition for automation.
INPUTS OVERVIEW
- Swing pivot left/right bars: swing sensitivity.
- Nesting ratio band (ratLo/ratHi): how close in scale the small leg must be to the big leg.
- Min big leg (x ATR) and ATR length: minimum move and volatility scaling.
- TP R multiple, SL buffer (x ATR), min bars between signals, one-trade-at-a-time.
- Visual colors, label offset, and zone transparency.
HOW TO USE
1. Add to any liquid symbol and timeframe; start with defaults.
2. Tighten the nesting-ratio band for stricter self-similarity, or widen it for more signals.
3. Raise Min big leg (x ATR) to demand larger, cleaner declines before a nest counts.
4. Use the drawn TP/SL zones for context; set an alert on the signal for hands-off monitoring.
5. Combine with your own trend/context read before acting.
LIMITATIONS
- This is a pattern/education tool, not a signal service, and not financial advice.
- Breakdown patterns fail; nesting geometry is a filter, not a guarantee. Losing signals will occur.
- Pivot confirmation adds inherent lag (it needs bars to the right of a swing to confirm).
- Very choppy or illiquid markets can produce misshapen legs and weak signals.
- Requires user discretion, risk management, and position sizing. No performance is implied.
CREDITS
The name is an inspirational sports homage only; it does not imply any endorsement or affiliation.
ATR uses Wilder's average true range. Pivot/zigzag swing detection uses standard public techniques.
The fractal-nest (scaled self-similar leg) geometry, the detection assembly, and the trade/zone
visualization are original Viprasol work.
Original Viprasol work; no third-party Pine code reused.
Indikator
