ATC Money Flow OscillatorWhat It Is
The ATC Money Flow Oscillator is a volume-weighted buying and selling pressure tool that tells you not just whether money is flowing in or out of an instrument, but how extreme that pressure is relative to recent market history. It is a normalized oscillator — which means its readings are statistically meaningful regardless of the asset, timeframe, or market conditions you apply it to.
Where most retail money flow tools give you a raw reading against a fixed threshold (and those thresholds are always wrong for someone, somewhere, at some point in time), the ATC MFO gives you a Z-score — a measurement of how far current pressure deviates from the rolling statistical baseline for that specific instrument and session. The result is an oscillator that speaks the same language whether you are trading ES futures on a 5-minute chart or GC on a 1-hour chart.
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Who It Is Built For
The ATC Money Flow Oscillator is built for traders who want a pressure confirmation tool that does not lie to them at the edges. If you have ever used Chaikin Money Flow, On Balance Volume, or a standard CMF and felt frustrated that the indicator screams "extreme" when conditions are perfectly normal, or gives a flat reading during a genuine momentum surge, this indicator was engineered specifically to solve that problem.
It works well as a standalone directional filter and as a confirmation layer for price action, trend, or breakout strategies. It is particularly useful for traders who want to know whether volume is supporting the move or quietly fading it before they commit to an entry.
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Core Concept
The foundation of the ATC MFO is a Chaikin-style money flow calculation. For each bar, it asks a simple question: where did price close within the bar's high-to-low range, and how much volume was behind that close? A bar that closes at the high of its range with heavy volume is strong buying pressure. A bar that closes at the low of its range with heavy volume is strong selling pressure. A bar that closes in the middle, or closes at the high with minimal volume, is ambiguous.
That per-bar measurement is called the Money Flow Multiplier — it produces a signed value between -1 and +1 for every bar, which is then multiplied by volume to create a Money Flow Volume reading. Those per-bar readings are summed over a rolling lookback window (default 10 bars) to build a directional picture of recent pressure, then divided by total volume in the same window to normalize for volume magnitude. The result is the raw Money Flow Ratio — a clean directional reading of where participation-weighted price activity is clustering.
That raw ratio is what most retail tools stop at. The ATC MFO treats it as the starting point.
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ATC MFO Upgrades
1. Z-Score Normalization
The raw Money Flow Ratio is run through a rolling Z-score calculation over a configurable normalization window (default 40 bars). This computes the rolling mean and standard deviation of the raw ratio across recent history and expresses the current reading as a number of standard deviations from that average. The result is the Money Flow Z-Score — the main oscillator line you see on the chart.
This single upgrade changes the character of the tool entirely. Instead of asking "is the reading above 0.25?" it asks "is the reading more than one standard deviation above average for this instrument in this session?" That is a meaningfully different and more honest question. The empirical pressure bands (at ±1 sigma and ±2 sigma) replace the guesswork of fixed thresholds with statistically derived extremes.
2. HMA Signal Line
Most money flow tools use an SMA or EMA signal line. The ATC MFO uses a Hull Moving Average (HMA) for signal smoothing. HMA dramatically reduces the lag that makes conventional smoothed signal lines late by design. The signal line updates faster, tracks direction more accurately through transitions, and avoids the "stale signal" problem where the smoothed line is still pointing one way while price has already reversed. The default HMA length is 6 bars, derived from the same optimization sweep as the lookback and normalization window settings.
3. Hysteresis-Stabilized State Engine
The indicator classifies the current pressure environment into five states: Neutral, Elevated Buying, Extreme Buy Pressure, Elevated Selling, and Extreme Sell Pressure. These states are displayed in the HUD and drive the color logic across the chart. Rather than flickering between states every time the Z-score crosses a threshold by a fraction, the state engine applies a configurable hysteresis band. Once you enter a state, you stay in it until pressure falls meaningfully below the threshold — not just one tick below it. This prevents the visual noise that makes most state-classifying indicators unreliable to read in real time.
4. Session Participation Tracker
The indicator maintains a live volume participation ratio: the current bar's volume expressed as a multiple of the session average volume for that day. A reading of 1.0x means volume is exactly in line with the session average. A reading above 1.20x means the current bar is printing above-average participation, which gives additional weight to whatever the pressure reading shows. A reading below 0.80x flags a low-participation bar — useful context when a pressure signal appears but volume is not backing it. This data lives in the HUD and updates every bar within the active session.
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Chart Visuals
Oscillator Line
The main oscillator is the Money Flow Z-Score plotted as a continuous line against the zero axis. The line is colored green when pressure is bullish and red when bearish, with the intensity of the color constant across both states. A soft glow layer behind the line (toggleable) reinforces the directional reading without adding clutter.
Zero Line
The zero line is the neutral dividing line between net buying and net selling pressure. Crossings of the zero line are meaningful — they mark the shift from net bullish participation to net bearish, or vice versa — and have dedicated alert conditions.
HMA Signal Line
The blue signal line is the HMA-smoothed version of the Z-score. It acts as a direction filter and a trend reference for the oscillator. When the oscillator is above the signal line and both are rising, pressure alignment is confirmed. When the oscillator crosses below the signal line, it is an early sign of deterioration even if the oscillator itself has not crossed zero yet.
Sigma Bands
Four reference lines mark the ±1 sigma and ±2 sigma levels. The inner bands (dashed) mark elevated pressure territory — statistically significant, but not extreme. The outer bands (solid) mark extreme pressure readings — statistically uncommon and historically associated with either climactic moves or exhaustion.
Zone Fills
Optional background shading between the sigma bands makes the pressure regimes immediately readable at a glance. A subtle green zone fills the space between the +1 and +2 sigma lines. A subtle red zone fills the space between the -1 and -2 sigma lines. A neutral grey zone fills the space between the inner bands. These fills have no impact on calculations — they are purely visual navigation aids.
Pressure Fill
An optional fill between the oscillator line and the zero line provides instant directional context. Green fill above zero, red fill below zero. This is particularly useful when the oscillator is making small movements near the zero line where directional color alone is harder to read quickly.
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HUD Breakdown
The HUD renders as a corner table (default position: top right, toggleable to any corner). It provides a live read of the five most important data points from the indicator without requiring you to hover over the chart or consult the data window.
State — The current pressure classification based on the hysteresis-stabilized state engine. Reports one of: Neutral, Elevated Buying, Extreme Buy Pressure, Elevated Selling, or Extreme Sell Pressure. The cell background color is green for bullish states, red for bearish, and muted blue for neutral.
Z-Score — The current Money Flow Z-Score expressed in sigma units to two decimal places. This is the raw number behind the oscillator line. Positive values indicate above-average buying pressure; negative values indicate above-average selling pressure. The cell background reflects the current pressure regime.
Signal — The current direction of the HMA signal line: Rising, Falling, or Flat. This one-word read tells you at a glance whether the smoothed pressure trend is accelerating, decelerating, or transitioning.
Participation — The current bar's volume expressed as a multiple of the session average. Displayed to two decimal places with an "x" suffix (e.g., 1.43x). Green when above 1.20x, red when below 0.80x, neutral otherwise.
Windows — Displays the active lookback and normalization window settings in the format "10 / 40z" so you can immediately see what calculation parameters are in play without opening the settings panel.
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Logic Layers
The indicator operates across three stacked logic layers that work together:
Layer 1 — Pressure Generation. Per-bar money flow multiplier × volume, summed over the lookback window and normalized by total volume. This produces the raw directional reading before statistics are applied.
Layer 2 — Statistical Normalization. The raw ratio is run through the rolling Z-score against the normalization window. This converts the raw reading into a statistically scaled value that is instrument-agnostic and session-aware.
Layer 3 — State Classification. The Z-score is classified into one of five pressure states using the hysteresis-stabilized threshold logic. This state drives the HUD display, color outputs, and alert logic.
The session participation tracker runs as a parallel calculation that does not influence the oscillator itself — it is purely a context layer that adds interpretive weight to whatever the main oscillator is showing.
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Alerts
The ATC MFO includes four alert conditions. All fire on state transitions or zero-line crosses, not on every bar within a given state. This means you will never get spammed with alerts while an existing condition persists — alerts only fire at the moment something changes.
MFO: Extreme Buying Pressure — Fires when the pressure state transitions into Extreme Buy territory (Z-score crosses above the outer sigma band). This marks a statistically significant acceleration of buying participation.
MFO: Extreme Selling Pressure — Fires when the pressure state transitions into Extreme Sell territory (Z-score crosses below the outer sigma band). This marks a statistically significant acceleration of selling participation.
MFO: Zero-Line Cross Up — Fires when the Z-score crosses above zero — the moment when net buying pressure emerges after a net bearish reading.
MFO: Zero-Line Cross Down — Fires when the Z-score crosses below zero — the moment when net selling pressure emerges after a net bullish reading.
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How to Trade With It
The ATC Money Flow Oscillator is not a signal generator. It does not tell you when to buy or sell. It tells you what participation-weighted pressure is doing so you can make better decisions about the trades your other analysis is already identifying. Use it as a confirmation and context layer.
Step 1 — Establish your directional bias. Use your preferred method — price structure, trend analysis, key levels, or market context — to identify the direction you are considering trading. The MFO confirms or contradicts that bias.
Step 2 — Check the Z-score and state. Before entering a trade, look at the HUD State and Z-Score readings. For a long entry, you want to see the state reading Neutral, Elevated Buying, or Extreme Buy Pressure, and the Z-score above zero. For a short entry, the inverse applies. If you are looking for a long and the MFO shows Elevated Selling, consider waiting for pressure to realign.
Step 3 — Check the signal line direction. The HMA signal line direction (shown in the HUD as Rising, Falling, or Flat) tells you whether pressure is accelerating or decelerating. The strongest confirmation is when the oscillator is above zero, the state is bullish, and the signal is rising. The weakest setup is when the oscillator and signal are diverging.
Step 4 — Check participation. Look at the Participation reading in the HUD. A pressure signal with 1.3x or higher participation means volume is actively supporting the move. A pressure signal with 0.7x participation means the move is happening on thin volume — be cautious about the sustainability of that signal.
Step 5 — Use the sigma bands for context. Readings near the outer sigma bands (+2 or -2) indicate extreme conditions. This can mean two things depending on context: either you are seeing climactic momentum that is likely to continue briefly before exhausting, or you are seeing exhaustion that is setting up a reversal. Use price structure to distinguish. In trending conditions, extreme readings in the direction of the trend are continuation signals. In range-bound conditions, extreme readings against key levels are often fading opportunities.
Step 6 — Use the zero-line cross alerts as context shifts. The zero-line cross alerts are useful as early-warning notifications that the character of participation is changing, even before price structure confirms it. A zero-line cross up while price is still above a key support level is a useful heads-up that buyers are reasserting. A zero-line cross down while price is approaching resistance is worth noting.
Step 7 — Do not fight extreme readings. When the MFO is printing Extreme Buy or Extreme Sell Pressure and the signal line is confirming, the path of least resistance is in that direction. The most common mistake traders make with normalized oscillators is fading strong readings too early. A +2 sigma reading does not mean the pressure is about to reverse — it means pressure is statistically extreme, and statistically extreme trends tend to resolve either through continued momentum or a period of neutralization before the next move.
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Settings Reference
Core Calculation
• Money Flow Lookback (default 10) — Bars used for the rolling money flow sum. Shorter values make the oscillator more responsive to recent bars; longer values smooth out intrabar noise. The default of 10 was derived from a full optimization sweep on QQQ at 1-minute resolution.
• Z-Score Normalization Window (default 40) — The rolling window used to compute the mean and standard deviation for Z-score scaling. This determines how "recent" the statistical baseline is. 40 bars is the optimized default; increasing this anchors the baseline to a longer history.
• Signal Line HMA Length (default 6) — The HMA smoothing length for the signal line. Shorter values produce a more reactive signal line; longer values produce a smoother one. HMA is used instead of SMA or EMA to minimize lag.
Pressure Bands (Sigma)
• Inner Band (default 1.0 sigma) — The threshold for Elevated Buying and Elevated Selling states. Readings beyond this line are statistically significant relative to the rolling window.
• Outer Band (default 2.0 sigma) — The threshold for Extreme Buy and Extreme Sell states. Readings beyond this line are statistically uncommon.
• State Hysteresis (default 0.10 sigma) — The neutral buffer applied to state transitions. Prevents the HUD state label from flickering when the Z-score is hovering near a threshold.
Session
• Session (default 0930-1600) — The session window used for the participation tracker and session-aware logic.
• Session Timezone (default America/New_York) — The timezone applied to the session definition.
Instruments and Timeframes
The ATC Money Flow Oscillator is validated and recommended for use on the following instruments and timeframes.
Instruments: ES, NQ, CL, GC, SPY, QQQ, major equities, major FX pairs.
Timeframes: 1-minute, 5-minute, 15-minute, 1-hour, 4-hour, Daily.
The indicator functions correctly on any instrument and timeframe that carries volume data. It is not suitable for instruments without volume reporting, such as some spot FX feeds.
Indicator
Expansion Target Planner [AGPro Series]Expansion Target Planner
🧠 Core Idea
After expansion is confirmed, where is the reasonable target band, how clean is the path, and what should be reviewed next?
📌 Overview / What it does
Expansion Target Planner is a chart-first risk-target planning tool designed to evaluate the target area after a confirmed range expansion.
Instead of drawing a generic target line or copying a measured-move pattern, the script studies the prior range edge, current ATR, continuation pressure, recent structure obstacles, volatility state, and an invalidation shelf behind the move. It then converts that context into a 0-100 Target Quality score and a clear next-action state.
The output is a practical planning workflow: an expansion target band, invalidation shelf, target midpoint guide, path obstruction marker, compact chart labels, alert conditions, and a clean AGPro decision panel. It does not predict the future, automate decisions, or guarantee that any target band will be reached.
🎯 Purpose & Design Philosophy
This script was built for traders who need a cleaner way to evaluate expansion targets after price has already shown confirmation.
Many tools focus on finding a breakout, drawing an equal measured move, or plotting fixed take-profit levels. This tool fills a different gap: it asks whether the next target area is reasonable, whether the path is blocked, and whether the invalidation reference still supports the plan.
The design supports a disciplined target-review mindset. It helps users separate a clean expansion path from a stretched, obstructed, expired, or invalidated plan.
⚡ Why This Script Is Different
Most tools focus on measured moves, ABCD projections, fixed target ladders, or generic breakout confirmation.
This script does NOT become a measured-move projection tool, ABCD pattern detector, take-profit ladder, auto trading system, or generic support/resistance map.
Instead, it builds one active expansion target plan after confirmation and evaluates the quality of that plan. The core output is not a trade command. It is a planning state that helps users review whether the target band, invalidation shelf, volatility, and structure path still make sense.
⚙️ Methodology
1. Context Detection
The script identifies whether price has confirmed expansion beyond a prior range edge. Users can keep the side on Auto or force Long Expansion / Short Expansion.
2. Reference Mapping
Once confirmation appears, the script locks an active target plan. It maps the expansion anchor, ATR-adjusted target distance, target band, invalidation shelf, and recent pivot-based path obstacle.
3. Reaction Evaluation
The script scores the plan using expansion strength, ATR projection fit, nearby structure, continuation pressure, volume support, trend support, and volatility state.
4. Visual Output
The chart displays the active target band, invalidation shelf, guide lines, obstruction marker, event labels, alerts, and AGPro panel state.
🗺️ How to Read the Chart
Zones = the forward target band and the invalidation shelf behind the expansion.
Labels = the current target planning state, such as TARGET READY, WATCH, OBSTRUCTED, TARGET HIT, or INVALID REVIEW.
Colors = green/teal supports cleaner bullish expansion quality, pink marks bearish or risk states, yellow marks caution or obstruction, and indigo is used as a neutral planning accent.
Panel = the compact decision view showing Expansion Side, Target Band, Invalidation, Target Quality, and Action.
🚦 Signals & States
• TARGET READY → the target band has acceptable quality and the path is clean enough for review.
• WATCH → target context is improving, but not enough conditions are aligned yet.
• OBSTRUCTED → a recent structure obstacle sits between current price and the target band.
• TARGET HIT → price has interacted with the active target band.
• INVALID REVIEW → price has crossed the invalidation shelf and the plan should be reviewed.
• EXPIRED → the active plan has spent too many bars without completing.
🔔 Alerts Logic
Alerts trigger when the active target state changes into an important review condition.
• Target Ready alert → target quality moves into a stronger review state.
• Target Watch alert → target context improves but remains incomplete.
• Path Obstructed alert → a structure obstacle blocks the target path.
• Target Band Touched alert → price reaches the active target band.
• Invalidation Review alert → price crosses the invalidation shelf.
Alerts are attention markers, not trade instructions.
🧩 Confluence Logic
The Target Quality score improves when expansion confirmation, ATR projection fit, continuation pressure, volume support, volatility state, and open structure path align.
When the target distance is reasonable, the close is efficient, volume supports the move, and no nearby obstacle blocks the path, the context becomes stronger.
📊 When to Use
• After confirmed range expansion
• During breakout continuation review
• When evaluating whether a target area is too close, too far, or structurally blocked
• When a trader wants target context without a fixed take-profit ladder
• During volatility expansion phases where target planning matters more than another signal
⚠️ When NOT to Use
• Very low-liquidity markets
• Extremely noisy sideways chop
• News-driven spikes where ATR and structure become unstable
• Markets with unreliable volume if volume support is central to your process
• Any situation where the user expects automatic trade instructions
🎛️ Key Inputs
• Expansion Side → Auto, Long Expansion, or Short Expansion planning.
• Prior Range Lookback → defines the range edge used for confirmation.
• Confirmation Break ATR → controls how far beyond the range edge price must close.
• Range Projection Multiple → adjusts how much prior range width contributes to the target distance.
• ATR Projection Multiple → adjusts how much current volatility contributes to the target distance.
• Target Band Width ATR → controls the visual width of the target band.
• Invalidation Shelf Lookback → defines the reference shelf behind the expansion.
• TARGET READY / WATCH thresholds → control how selective the state engine is.
• Visual settings → control target band, shelf, guide lines, obstruction marker, labels, panel location, theme, and font sizes.
🖥️ Interface & Visual Design
The interface is built around one active target plan.
The target band is displayed forward on the chart with centered text. The invalidation shelf is shown behind the move so the risk reference is visible without turning the script into a generic support/resistance tool.
The panel follows the AGPro public-release standard with one merged blue header row containing only the script name. The layout is compact and designed for quick reading during live chart review.
🧪 Practical Usage Workflow
1. Read the panel to identify the active Expansion Side and Target Quality.
2. Check whether the target band is clean or obstructed.
3. Review the invalidation shelf behind the expansion.
4. Use labels and alerts as attention markers.
5. Confirm the broader market context with your own process.
🔍 Interpretation Guidelines
Treat the target band as a planning area, not a guaranteed destination.
A higher Target Quality score means the target plan is cleaner according to the script rules. It does not mean the move must continue.
An OBSTRUCTED state does not mean price cannot move through the obstacle. It means the path contains structure that deserves review.
An INVALID REVIEW state means the active shelf has been crossed and the plan context has changed.
🚫 What This Script Is NOT
• Not a prediction engine
• Not financial advice
• Not auto trading
• Not guaranteed signals
• Not a measured-move projection system
• Not an ABCD pattern scanner
• Not a take-profit ladder
⚠️ Limitations & Transparency
• Timeframe differences can change expansion quality and target distance.
• Volatility shifts can make a previously clean target band less useful.
• Recent structure may not capture every important higher-timeframe obstacle.
• Volume-based scoring can be less useful on symbols with unreliable volume.
• No rule-based tool can fully account for news, liquidity shocks, or sudden regime changes.
🧠 Market Context Notes
Expansion targets are more useful when the market has already shown range release and the target path is not immediately blocked by nearby structure.
Liquidity, volatility, and structure should be read together. A target band can look reasonable by distance but still become lower quality if the path is obstructed or volatility becomes overheated.
🧾 Use Case Examples
When price closes beyond a prior range edge with strong close location and the target path is open, the script may show TARGET READY.
When price expands but a recent pivot sits directly between current price and the target band, the script may show OBSTRUCTED.
When price crosses the invalidation shelf behind the plan, the script may show INVALID REVIEW.
🧱 System Philosophy
AGPro Series tools are designed to support structured decision review, not emotional signal chasing.
This script follows that philosophy by focusing on target quality, invalidation context, and next-action state rather than a simple directional signal.
🔐 Non-Promise Statement
No target band is certain.
No score guarantees continuation.
No alert should be treated as a trade instruction.
📉 Risk Disclosure
Trading involves risk.
Users are responsible for their own decisions, position sizing, risk controls, and market interpretation.
This script is for educational and analytical use only and does not provide financial advice.
📚 Educational Note
Use this tool to study how target quality changes after expansion confirmation.
The strongest value comes from comparing the target band, obstruction marker, invalidation shelf, and broader market context together.
Indicator
No-Progress Failure Map [AGPro Series]No-Progress Failure Map
🧠 Core Idea
Did price trigger a setup but fail to travel far enough afterward?
📌 Overview / What it does
No-Progress Failure Map is a post-trigger execution failure planner designed to evaluate whether an active setup is actually moving after it triggers, or simply stalling around the trigger area.
The script builds a progress window, maps a risk shelf, projects a minimum progress rail, tracks elapsed bars, measures distance travelled in ATR, evaluates candle efficiency, reads volume participation, and converts the result into a 0-100 Progress Score with a clear action state.
It does not predict price direction, automate trading, or print guaranteed entry or exit commands. Its purpose is to organize the question of progress versus failure after a trigger appears.
🎯 Purpose & Design Philosophy
This script was built for traders who do not want to judge a setup only at the moment it triggers.
Many setups look valid at first, but the real weakness appears later: price does not travel far enough, time passes, participation fades, or the trigger side is lost. This tool turns that hidden execution problem into a visible decision layer.
It supports a planning mindset: trigger, observe progress, evaluate time cost, check failure risk, and decide what deserves attention next.
⚡ Why This Script Is Different
Most tools focus on finding the trigger itself.
This script does NOT behave like a generic signal indicator, opening range failure tool, RSI failure swing detector, order-block map, support/resistance scanner, or broad regime dashboard.
Instead, it asks a narrower execution question: after a setup starts, is price travelling enough to keep the idea alive, or is the setup becoming a no-progress failure?
⚙️ Methodology
1. Context Detection
The script selects the evaluation side using Auto, Long Context, or Short Context. Auto mode follows trend and slope context.
2. Trigger Mapping
The planner starts a tracking window from a selected trigger model: Range Break, Impulse Close, or Trend Reclaim.
3. Progress Evaluation
It measures favorable travel, elapsed bars, close efficiency, relative volume, time decay, reclaim behavior, and risk shelf pressure.
4. Visual Output
It displays a stalled-move box, minimum progress rail, risk shelf, trigger line, event labels, alerts, and a compact AGPro panel.
🗺️ How to Read the Chart
Zones = the stalled-move box between the risk shelf and the minimum progress rail.
Labels = compact event markers for Trigger, No Progress, Reclaim, Travel OK, and Failed states.
Colors = teal marks accepted progress, pink/red marks failure or invalidation, amber marks stalled progress, and indigo marks active watch or recovery context.
Panel = summarizes Progress Score, Elapsed Bars, Distance Travelled, Failure Risk, and Action.
🚦 Signals & States
• Trigger → a new post-trigger progress window is active.
• Watch Progress → the setup is active but has not yet proven enough travel.
• Stalled → price has lost the trigger side or is not progressing cleanly.
• No Progress → the evaluation window matured without enough favorable travel.
• Reclaim → price recovered the trigger side after temporary loss.
• Travel OK → the setup reached the accepted progress threshold.
• Failed → the tracked setup crossed its risk shelf.
🔔 Alerts Logic
Alerts trigger when a new progress window starts, when no-progress failure risk appears, when travel is accepted, when a reclaim appears, or when the risk shelf is crossed.
Alerts are attention markers. They are not trade instructions, automated strategy commands, or certainty signals.
🧩 Confluence Logic
The strongest progress context appears when favorable travel, close efficiency, volume participation, time efficiency, and trigger-side control align.
When travel is weak and elapsed bars increase, the failure-risk reading rises. When the trigger side is lost and reclaimed, the script marks recovery context but does not treat it as certainty.
📊 When to Use
• After a breakout-style trigger appears.
• During continuation attempts that should show progress quickly.
• Around trend reclaim setups where follow-through matters.
• When a setup looks active but price remains trapped near the trigger.
• On liquid markets where ATR and relative volume are meaningful.
⚠️ When NOT to Use
• Extremely low-liquidity markets with unreliable candles or volume.
• Very noisy micro-timeframes where trigger-side loss is frequent.
• News-driven volatility spikes where ATR expands suddenly.
• Symbols where volume data is missing or not useful.
• As a standalone reason to enter, exit, or size a trade.
🎛️ Key Inputs
• Evaluation Side → controls Auto, Long Context, or Short Context.
• Trigger Model → selects Range Break, Impulse Close, or Trend Reclaim activation.
• Evaluation Window Bars → defines how long the setup has to show minimum progress.
• Minimum Progress ATR → defines the expected favorable travel threshold.
• Progress Accepted ATR → defines stronger follow-through.
• Risk Shelf Buffer ATR → controls invalidation distance around the initial shelf.
• Visual Settings → control boxes, rails, prior boxes, labels, panel location, theme, and font sizes.
🖥️ Interface & Visual Design
The interface is chart-first.
The stalled-move box is the primary visual object and contains a centered progress meter. Rails show trigger, risk, and progress references without turning the chart into a crowded level map.
The panel follows the AGPro publication layout with a single merged blue title row, adjustable location, adjustable theme, and adjustable font size.
🧪 Practical Usage Workflow
1. Read the panel state and Progress Score.
2. Check whether price is travelling beyond the minimum progress rail.
3. Review elapsed bars versus the evaluation window.
4. Watch for No Progress, Reclaim, Travel OK, or Failed labels.
5. Interpret the output inside broader market structure and risk context.
🔍 Interpretation Guidelines
A high Progress Score means the setup is moving efficiently relative to this rule set. It does not mean price must continue.
A No Progress label means the setup has not travelled enough after the selected trigger. It does not guarantee failure, but it highlights weakening execution quality.
A Failed state means the mapped risk shelf was crossed. It should be read as rule-based invalidation context, not as financial advice.
🚫 What This Script Is NOT
• Not a prediction engine.
• Not financial advice.
• Not auto trading.
• Not guaranteed signals.
• Not a buy/sell signal service.
• Not an opening range failure tool.
• Not an RSI failure swing detector.
• Not a generic support/resistance or order-block map.
⚠️ Limitations & Transparency
Progress quality depends on the selected trigger model, lookback, ATR length, timeframe, and market conditions.
Different symbols may produce different volume behavior. High volatility can expand the tracking box quickly, while low volatility can make progress thresholds harder to interpret.
The script is rule-based and should be used as an analytical planning layer, not as a complete trading system.
🧠 Market Context Notes
No-progress behavior is often a time and efficiency problem, not just a price-level problem.
A setup can trigger, remain technically alive, and still become unattractive if it fails to move far enough while time passes. This script makes that condition visible.
🧾 Use Case Examples
When price breaks a recent range but remains near the trigger after the evaluation window, the map can mark No Progress and increase failure risk.
When price loses the trigger side and then reclaims it, the script can mark Reclaim so the user can review whether recovery is meaningful.
When price travels beyond the accepted progress threshold with efficient closes, the panel can move toward Travel OK context.
🧱 System Philosophy
No-Progress Failure Map follows the AGPro decision-engine approach: the script should help users evaluate context, quality, risk, progress, and next action without promising an outcome.
The goal is not to add another signal. The goal is to make post-trigger progress easier to judge.
🔐 Non-Promise Statement
No script can guarantee direction, continuation, reversal, or outcome.
This tool provides structured chart context only.
📉 Risk Disclosure
Trading involves risk.
Users are responsible for their own analysis, risk controls, position sizing, and trading decisions.
This script does not provide financial advice, investment advice, or guaranteed trading outcomes.
📚 Educational Note
Use the script to study how triggered setups behave after activation. The most useful reading comes from comparing progress, elapsed bars, risk shelf behavior, and broader market context.
Indicator
ATC Keltner Channel Breakout System v1.3.0What It Is
The ATC Keltner Channel Breakout System (ATC KCBS) is a breakout detection indicator built on one of the most reliable structural tools in technical analysis — the Keltner Channel — and rebuilt from the ground up to meet a higher quality standard.
Most retail Keltner indicators do one thing: draw a channel and let you guess when a breakout means something. The ATC KCBS does something different. It filters every breakout signal through a volume confirmation gate built on Z-score normalization, so the only breakouts that get flagged are the ones backed by real, statistically significant participation — not routine price noise pushing outside the bands on low volume.
The result is a cleaner, higher-quality signal set that respects your time and your capital.
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Who It's Built For
The ATC KCBS is designed for active traders focused on momentum breakouts — particularly on U.S. equities, index ETFs (QQQ, SPY), and futures (ES, NQ, CL, GC) during regular trading hours. It performs best on the 1-minute through 15-minute timeframe for intraday traders, and scales cleanly up to the 1-hour, 4-hour, and daily timeframes for swing traders. Default settings are optimized for QQQ on the 1-minute chart during RTH (Regular Trading Hours).
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The Core Concept: What Is a Keltner Channel?
A Keltner Channel consists of three lines plotted directly on your price chart:
• A basis line — a smoothed moving average of price, acting as the channel's center of gravity
• An upper band — the basis plus a multiple of the Average True Range (ATR)
• A lower band — the basis minus that same ATR multiple
When price is inside the channel, the market is respecting the channel's structure and typically moving in a mean-reverting or consolidating mode. When price closes outside either band, it signals that a breakout condition may be developing. The distance of the bands from the basis is dynamic — they widen during volatile markets and compress during quiet ones.
The Keltner Channel is a better volatility envelope than Bollinger Bands for many breakout applications because ATR measures directional price movement rather than raw price deviation, which makes the channel walls more responsive to real market conditions.
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The Upgrade: What Makes This Different
Retail Keltner indicators treat all breakouts the same. A close above the upper band is a signal — end of story. The problem is that the majority of Keltner band breaks are low-conviction moves driven by thin conditions, choppy price action, or noise — not real directional momentum.
The ATC KCBS adds two meaningful upgrades over the generic version:
1. HMA-Smoothed Basis
The channel's center line uses a Hull Moving Average (HMA) instead of the standard simple moving average (SMA) or exponential moving average (EMA) found in most retail Keltner tools. HMA smoothing reduces lag without sacrificing responsiveness, so the basis line tracks price structure more accurately — and the channel bands it drives are positioned more precisely as a result.
2. Z-Score Normalized Volume Gate
This is the core enhancement. Before any breakout gets confirmed, volume on that bar is measured against a rolling statistical baseline — specifically, a Z-score calculated against the trailing volume mean and standard deviation. A breakout only gets flagged if volume is sufficiently elevated above that baseline in statistical terms.
This matters because a price close above the upper band with average or below-average volume is a very different event than the same close accompanied by a volume spike that is statistically exceptional relative to recent conditions. The volume gate filters the noise and focuses your attention on breakouts that have real conviction behind them.
You can toggle the volume gate on or off and adjust the Z-score threshold directly in the indicator settings.
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What You See on the Chart
The ATC KCBS overlays directly on your price chart and renders the following:
The Channel
Three lines form the Keltner structure: the HMA basis in gold, and the upper and lower bands flanking it. The interior of the channel fills with a subtle color that reflects the current market state, making it easy to see at a glance whether conditions are bullish, bearish, compressing, or expanding.
Regime Color Coding
The channel fill, band colors, and background tint all update dynamically to communicate the current market regime:
• Green tones indicate an active bullish breakout bias
• Red tones indicate an active bearish breakout bias
• Blue tones indicate a channel expansion regime (rising volatility)
• Grey tones indicate a channel compression regime (contracting volatility, potential coiling before a move)
• Gold (default) indicates a neutral, ready state
This color system means you can scan your chart and immediately understand the context without reading anything. Green channel = bullish momentum active. Grey channel = market coiling.
Breakout Markers
When a confirmed breakout fires — meaning price has closed beyond the band AND volume has passed the Z-score threshold — the indicator places labeled markers directly on the chart at that bar. Bullish breakouts receive a green triangle and an "LONG" label. Bearish breakouts receive a red triangle and an "SHORT" label.
These markers only appear when both conditions are met. If the volume gate doesn't pass, no marker appears, even if price is outside the band.
Breakout Tags
In addition to the edge markers, the indicator plots branded "LONG CONFIRM" and "SHORT CONFIRM" labels near the breakout bar for additional visual clarity. You can control how many recent tags stay visible on the chart at one time via the settings.
Bar and Background Tinting
During an active breakout bias, candle bars are tinted with the direction color (green for bullish, red for bearish) to help you maintain context as the bias holds. A subtle background tint reinforces the same state. Both are individually toggleable if you prefer a cleaner look.
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The HUD (Heads-Up Display)
The ATC KCBS contains a HUD panel that surfaces live data without cluttering your chart. The ATC KCBS HUD displays:
• Live State — the current overall status of the indicator, displayed prominently in the header row. Possible values: BULLISH, BEARISH, COMPRESSION, EXPANSION, or READY.
• Bias — whether a breakout bias is currently active, and how many bars remain in the bias hold window.
• Regime — the current channel regime (Compression, Expansion, or Neutral).
• Location — where price is relative to the channel right now: Inside Channel, Outside Upper, or Outside Lower.
• Price vs Basis — whether price is currently above or below the HMA basis, expressed in ticks for precision.
• Vol Gate — the real-time status of the volume gate. Shows PASS with the current Z-score when the threshold is met, or WAIT with the current Z-score when it is not. This is one of the most useful readouts in the HUD — it tells you exactly how close volume is to confirming the next breakout signal.
• Width — current channel width expressed in ticks.
• Width Z — the Z-score of current channel width relative to its own rolling history. Negative values indicate the channel is narrower than usual (compression). Positive values indicate it is wider than usual (expansion).
The HUD is available in dark and light themes and can be positioned in any corner of the chart.
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The Regime Engine
Beneath the visual layer, the ATC KCBS tracks a volatility regime state based on where the channel width Z-score sits relative to empirically-derived thresholds. This is not a binary switch — the regime uses a hysteresis band to prevent false flickering at the threshold boundaries.
• Compression is flagged when channel width drops significantly below its historical
average, indicating the market is coiling. Compression is often a precursor to a sharp directional move. When you see COMPRESSION on the HUD and in the grey channel, the market is telling you it is building energy.
• Expansion is flagged when channel width rises significantly above its historical average, indicating volatility is increasing. Expansion during an active breakout is a confirmation of momentum. Expansion during a neutral bias can signal that conditions are becoming active.
• Neutral is the default state between compression and expansion.
These regime states are displayed in the HUD, reflected in the channel color, and feed directly into the overall live state displayed in the header row.
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The Breakout Bias Hold
When a confirmed breakout fires, the indicator does not simply mark the bar and reset. It sets an active directional bias that persists for a configurable number of bars (default: 5). During the bias hold window, the HUD shows the direction and the bars remaining in the hold. The channel and background colors reflect the active bias throughout.
The bias clears early if price returns inside the channel before the hold window expires. This gives you a simple, clean way to track whether post-breakout price action is confirming the move or reversing it.
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Alerts
The ATC KCBS includes two configurable alert conditions:
• Alert on Bullish Breakout — fires when a confirmed bullish breakout occurs (price closes above the upper band with volume gate passed)
• Alert on Bearish Breakout — fires when a confirmed bearish breakout occurs (price closes below the lower band with volume gate passed)
Both can be toggled independently. To use them, set up your alert in PulseWire and select the appropriate condition. The alert message includes the ticker and timeframe for easy identification in multi-alert setups.
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How to Trade With It
The ATC KCBS is a breakout signal tool. Its primary job is to tell you when a channel break has real participation behind it, and to maintain context about the market's current volatility regime. Here is a practical framework for using it:
Step 1 — Read the Regime First
Before anything else, check the regime. If the HUD says COMPRESSION and the channel is grey, the market is coiling. This is a waiting state — not a trading state. Watch for a breakout to develop as the regime transitions.
If the HUD says EXPANSION and the channel is blue, volatility is already elevated. Breakouts in expansion regimes tend to be more energetic but can also be more erratic. Confirmation from your other confluence tools matters more here.
Step 2 — Watch the Volume Gate
The Vol Gate row in the HUD is your pre-signal radar. When the market starts approaching the upper or lower band, watch the Vol Gate reading. If volume is already elevated (Z-score approaching or above the threshold), a breakout with confirmation is more likely. If volume is flat, a band touch is more likely to be noise.
Step 3 — Wait for the Confirmation Marker
Do not trade the touch of the band. Trade the confirmed close. A confirmed breakout is defined as: price closes beyond the band AND the volume Z-score exceeds the threshold. The "LONG CONFIRM" or "SHORT CONFIRM" label on the chart is your signal.
Step 4 — Assess Post-Breakout Price Action Within the Bias Hold
Once a confirmed breakout fires, monitor the bias hold countdown in the HUD. If price holds above the band (bullish) or below the band (bearish) during the hold window, the breakout is showing follow-through. If price returns inside the channel before the hold expires, treat it as a failed breakout and step aside.
Step 5 — Use the Channel as a Reference After Entry
After entering on a confirmed breakout, the HMA basis becomes your key reference level. The basis is a smoothed representation of where the market's center of gravity is. Price above the basis on a bullish breakout is good. Price that retreats to the basis quickly after the breakout is a warning.
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Settings Reference
The indicator's settings are organized into clearly labeled groups:
Channel Configuration — Controls the HMA basis length, ATR length, and ATR multiplier. The defaults are optimized for QQQ on the 1-minute chart. Increase the basis length for smoother, slower channel response on higher timeframes.
Volume Gate — Toggle the volume confirmation requirement on or off. Adjust the Z-score lookback window and threshold. The default threshold (3.6) is calibrated for the optimized QQQ 1-minute profile. On other instruments or timeframes, a threshold between 1.0 and 2.0 is typically a reasonable starting point.
Session — Set the trading session and timezone. Defaults to the U.S. Regular Trading Hours session (9:30 AM — 4:00 PM Eastern). Extended hours users should adjust accordingly.
Visuals — Control all color settings, fill opacity, glow opacity, background tint, and bar tinting. Every visual element is independently adjustable. ATC's default palette (green, red, gold, grey, blue) is applied by default.
Signal Styling — Set the breakout tag text color and the maximum number of recent breakout tags kept on the chart.
Alerts — Toggle bullish and bearish alert conditions independently.
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Intended Instruments and Timeframes
Validated for: ES, NQ, CL, GC (futures), SPY, QQQ (ETFs), major FX pairs, large-cap equities
Recommended timeframes: 1-minute, 5-minute, 15-minute, 1-hour, 4-hour, Daily
Default profile optimized for: QQQ, 1-minute, Regular Trading Hours
Indicator
Volatility Terrain Engine [JOAT]
Volatility Terrain Engine
Introduction
Volatility Terrain Engine is a pane-based oscillator that measures the current volatility regime using the ratio between a fast ATR and a slow ATR, combined with a percentile rank of current volatility within a historical window. The indicator classifies every bar into one of three states — Expansion, Compression, or Transition — and identifies squeeze conditions (volatility compressing well below its average) and expansion bursts (volatility accelerating rapidly). The oscillator, centered at zero, makes it immediately clear whether volatility is expanding or contracting relative to its baseline.
Volatility regime is one of the most underappreciated dimensions of market analysis. A trend-following strategy applied during volatility compression produces poor results because the market is not moving directionally with sufficient energy. A mean-reversion strategy applied during volatility expansion gets stopped out repeatedly because the market is generating outsized moves. Identifying the current volatility terrain before applying any strategy is a prerequisite for selecting the appropriate approach.
Core Concepts
1. Fast/Slow ATR Ratio
The primary oscillator compares a short-period ATR (default 14) against a long-period ATR (default 100). Their ratio, centered at 1.0, is shifted to center at 0.0 by subtracting 1. Values above 0 mean recent volatility is expanding relative to the longer-term baseline; values below 0 mean it is contracting. This ratio is more informative than ATR alone because it provides context — the same ATR value means different things in a historically volatile versus historically calm market.
2. Percentile Rank
The ATR percentile rank answers: where does today's volatility sit within its historical distribution? A 90th percentile reading means volatility is higher than 90% of observations in the lookback period. This is used to classify whether the current environment is historically extreme or within normal parameters.
3. Squeeze and Expansion Burst Detection
A squeeze is defined as fast ATR falling below 82% of slow ATR and also below its own 20-bar average. This double condition filters single-bar dips. A squeeze represents stored energy — the market is coiling. An expansion burst is defined as the ATR ratio exceeding 1.25 with the fast ATR making successive higher values. This marks the initial stages of a volatility explosion.
4. Signal Line and Histogram
The oscillator is triple-processed: EMA of ratio → SMA signal → histogram. The histogram shows the divergence between the oscillator and its signal, providing a leading read on whether volatility momentum is building or fading.
Features
Volatility Regime Oscillator: Gradient-colored histogram bars centered at zero
Squeeze Detection: Dashboard alert and dot marker when squeeze conditions are active
Expansion Burst Markers: Dot markers when volatility breaks out from compression
ATR Percentile Band: Normalized ATR rank plotted as a secondary line
Zone Fills: Expansion and compression zones filled with transparent color
8-Row Dashboard: Regime, ATR values, ratio, percentile rank, squeeze status, oscillator values
Input Parameters
Fast ATR Period: Short-term volatility measurement (default: 14)
Slow ATR Period: Long-term volatility baseline (default: 100)
Percentile Lookback: Historical window for rank calculation (default: 252)
Signal Smoothing: Signal line period (default: 9)
Expansion, Compression, and Transition color inputs
How to Use This Indicator
Compression → Expansion Transition
The most significant signal is when a squeeze resolves into an expansion burst. This represents a volatility state change — the market has been coiling and is now releasing energy. The direction of that release is not predicted by this indicator; it must be determined using price structure and other context.
Oscillator Zero Cross
The oscillator crossing from negative to positive territory indicates that short-term volatility has exceeded the long-term baseline. This is not a trade signal — it is a condition indicator confirming that the market is entering a higher-energy phase.
High Percentile + Expansion
When the oscillator is in expansion territory and the ATR percentile rank is above 80, the market is experiencing historically significant volatility. Stops must be sized accordingly.
Limitations
ATR is backward-looking. Sudden volatility spikes from news events will appear in the oscillator only after those bars close
The squeeze condition uses fixed multipliers (0.82 for the ATR ratio threshold). Markets with different typical volatility profiles may require adjustments to these thresholds
The percentile lookback of 252 bars requires approximately one year of daily data or equivalent for the rank to be historically meaningful. On shorter data sets the rank will be computed on whatever bars are available but will be less statistically robust
This indicator classifies current conditions only. It does not predict when a squeeze will resolve or in which direction
Originality Statement
The dual-ATR ratio approach combined with percentile ranking provides more contextual information than either measure alone. The squeeze detection using a double condition (ratio below threshold and below its own moving average) produces more reliable squeeze identification than a single-condition approach. The four-state histogram coloring (expanding positive, fading positive, expanding negative, fading negative) provides more nuanced momentum information than standard positive/negative coloring.
Disclaimer
This indicator is for educational and informational purposes only. Volatility regime classification does not predict price direction. A squeeze does not guarantee a subsequent expansion, and the direction of any expansion is unknowable from volatility data alone. Always use appropriate risk management.
-Made with passion by officialjackofalltrades
Indicator
DVOL based Bitcoin Volatility This indicator maps Bitcoin's expected price range across three timeframes — daily, weekly, and monthly — using the Deribit Volatility Index (DVOL) as the implied volatility source and realized historical volatility (HV7, HV14, HV30) as the measured counterpart.
DVOL is Bitcoin's equivalent of the VIX. It represents the market's forward-looking expectation of annualized volatility, derived from Deribit options pricing. When DVOL is high, the market expects large moves. When it is low, the market expects compression. By scaling DVOL and realized vol into dollar-denominated price bands anchored to key opens, this indicator gives you a structural volatility map directly on the BTC price chart — no separate pane required.
The core concept is straightforward: options market participants price expected ranges. Those ranges become levels. Price respects them — not always, not perfectly, but consistently enough to be meaningful as reference and used in comparison to what is realized.
How to Read the Bands
The Anchoring System
Each set of bands is anchored to a specific open and held fixed for its entire period. They do not drift or repaint mid-period.
**Weekly bands** lock on Saturday's opening price and DVOL reading at the start of each crypto week. They hold for the full 7-day period. This Saturday anchor matters: the crypto options and perpetuals market structurally resets around the Saturday UTC open. Weekly expiries settle on Fridays, and Saturday represents the cleanest "new week" anchor available on a 24/7 market.
**Monthly bands** lock on the 1st of each calendar month and hold for the entire month. They represent the options market's expectation of how far BTC could move over a 30-day window from that open.
**Daily bands** reset each day at 00:00 UTC and reflect that day's opening price and current live volatility readings. They are the tightest, most reactive bands on the chart.
The Band Pairs
Each timeframe shows two bands — one from implied volatility (IV) and one from realized historical volatility (HV):
**IV bands** (white weekly, white monthly) represent what the options market *expects* BTC to move. These are forward-looking. They define the market's priced range for the period.
**HV14 Weekly** (orange) represents the actual realized volatility over the past 14 days, scaled to a weekly move. When HV14 is inside the IV band, the market is pricing more risk than it has been delivering — a low-volatility regime. When HV14 approaches or exceeds the IV band, realized vol is catching up to or exceeding what was priced.
**HV30 Monthly** (orange-red) is the 30-day realized volatility scaled to a monthly move. This sits alongside the monthly IV band and gives context for whether the current month's implied range is historically generous or tight.
**HV7 Today** (light yellow) is a live daily band using the most recent 7 days of realized volatility anchored to today's open. It is the most sensitive reading — useful for intraday context and identifying when daily price movement is pushing into or through the short-term realized range.
**IV Today** (faded white) is the same daily scaling but using DVOL — today's implied daily range from the options market. It is intentionally faded to keep the chart readable.
The Info Table
The top-left badge shows three live readings updated on every bar:
- **IV %** — the current DVOL weekly reading with a heat emoji (🔥 above 60%, ❄️ below 40%, ⚡ in between)
- **HV14 %** — the Saturday-latched realized vol for the week
- **HV14/IV ratio** — the percentage of realized vol relative to implied. ✅ below 95% means RV is running below IV (options are pricing more than has been delivered). ⚠️ at or above 95% means RV is catching up to or exceeding IV — a higher-energy regime.
- **Daily change** — BTC price change from today's open in both % and dollar terms
The Saturday Anchor Line
The ⚓ Sat Open line marks the weekly anchor price. It is the midpoint of the weekly IV and HV14 bands. Price reclaiming or failing at this line is significant — it is the reference price that all weekly band math is built from.
Trend Channels
Two sets of dynamic trendlines auto-draw based on pivot structure — a shorter-period dashed pair and a longer-period solid pair. They update continuously as new pivots form. Green slope = bullish structure on that channel. Red slope = bearish. They reset on the 1st of each calendar month, giving enough bars to build meaningful structure across a full monthly cycle rather than resetting too frequently on the weekly.
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Settings Walkthrough
Display Toggles
✅ Show Weekly Open Line | The ⚓ Sat Open midline
✅ Show Weekly Bands (IV + HV14) | Both white IV weekly and orange HV14 bands together
✅ Show Monthly Bands (IV + HV30) | Both white IV monthly and orange-red HV30 bands together
✅ Show HV7 Today (daily rotating) | The light yellow daily realized vol band — resets each day
✅ Show IV Today (daily rotating) | The faded white daily implied vol band — resets each day
The weekly and monthly band pairs are intentionally linked — IV and HV are most useful when compared against each other, so they toggle as a unit.
Label Proximity Gate ($)
When multiple bands converge near the same price level, the chart can become cluttered with overlapping labels. The Proximity Gate controls how close a daily band label can be to a weekly or monthly level before it is suppressed. The **line still draws** — only the text label is hidden.
**Default: $200.** At this setting, a daily HV7 or IV Today label will be hidden if it sits within $200 of any weekly or monthly band. Increase this value if you want a cleaner chart with fewer labels. Decrease it if you want to see all labels even when levels are close together.
**Practical guidance:**
💡 On wider perspectives toggle HV7/IV (daily) off and widen 'proximity label gate' to reduce screen clutter
💡 On narrow perspectives keep the daily looks with a tighter 'proximity label gate'
Trend Line Settings
Short and long pivot periods are adjustable independently. The defaults (10 and 16) are calibrated for the 30-minute timeframe. On the 1-hour chart, consider reducing both slightly. On 15-minute, increasing them gives more stable pivots. Because the trendlines reset monthly rather than weekly, they have sufficient bars to establish meaningful channel structure — particularly useful for identifying multi-week compression patterns and directional bias across the full monthly vol cycle.
🚨 General — The indicator is most powerful when used to identify when price is testing a band confluence — for example, when the weekly IV lower and monthly HV30 lower are within close range of each other. Those areas represent options-market-defined support zones where two independent vol calculations agree.
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*Indicator is designed for BTCUSD. Requires access to DERIBIT:DVOL data on PulseWire. Works on intraday timeframes only — weekly and monthly band projections display for the current period.*
Indicator
Volatility Regime Engine [JOAT]Volatility Regime Engine
Introduction
The Volatility Regime Engine is a sophisticated volatility analysis tool designed to identify market cycles through expansion and contraction patterns. This indicator goes beyond simple volatility measurement by classifying volatility into distinct regimes, detecting squeeze patterns, and forecasting potential volatility shifts. It's built for traders who understand that volatility is not just noise but a predictable cycle that creates trading opportunities when properly understood.
Volatility is the lifeblood of markets - it creates opportunities, determines risk, and influences strategy selection. This engine provides institutional-grade volatility analysis that helps traders adapt their approach to current market conditions. Whether you're a day trader adjusting stop distances, a swing trader timing entries after volatility contractions, or a position trader sizing positions based on volatility forecasts, this tool provides the critical volatility intelligence needed for superior decision-making.
Why This Indicator Exists
Most traders treat volatility as a single number (like ATR) without understanding its cyclical nature and predictive properties. This indicator addresses that limitation by:
Regime Classification: Identifies whether volatility is expanding, contracting, or normal, allowing strategy adaptation
Squeeze Detection: Pinpoints volatility compression patterns that often precede significant price moves
Cycle Analysis: Tracks volatility cycles to identify optimal entry and exit timing
Forecasting Capability: Uses mean reversion principles to predict likely volatility shifts
Adaptive Multipliers: Provides dynamic stop loss and target multipliers based on current volatility
Historical Context: Places current volatility in percentile context for better decision making
The engine solves the critical problem of using static risk management in dynamic volatility environments. By understanding where you are in the volatility cycle, you can anticipate market behavior and position yourself accordingly.
Core Components Explained
1. Multi-Layer ATR Analysis
The indicator uses three ATR timeframes to capture volatility across different horizons:
// Multiple ATR timeframes
float atr_fast = ta.atr(i_atr_fast)
float atr_slow = ta.atr(i_atr_slow)
float atr_baseline = ta.sma(ta.atr(i_atr_slow), i_atr_baseline)
// ATR ratios
float atr_ratio = atr_baseline > 0 ? atr_slow / atr_baseline : 1.0
float atr_momentum = atr_fast / atr_slow
ATR layers:
Fast ATR (7 periods): Captures immediate volatility changes
Slow ATR (21 periods): Medium-term volatility trend
Baseline ATR (50 periods smoothed): Long-term volatility average
ATR Ratio: Current volatility relative to baseline (key for regime detection)
ATR Momentum: Short-term volatility acceleration/deceleration
The ATR ratio is the primary driver of regime classification - values above 1.4 indicate expansion, below 0.6 indicate contraction.
2. Squeeze Detection System
The indicator uses the classic TTM Squeeze concept with enhanced features:
// Squeeze state
bool squeeze_on = bb_lower > kc_lower and bb_upper < kc_upper
bool squeeze_off = bb_lower < kc_lower and bb_upper > kc_upper
// Squeeze duration tracking
var int squeeze_duration = 0
if squeeze_on
squeeze_duration := squeeze_duration + 1
else
squeeze_duration := 0
// Squeeze intensity (longer squeeze = more explosive release)
float squeeze_intensity = math.min(float(squeeze_duration) / 20.0 * 100, 100)
Squeeze components:
Bollinger Bands: Measure volatility through standard deviation
Keltner Channels: Measure volatility through ATR
Squeeze On: BB inside KC indicates volatility compression
Squeeze Duration: Time in compression - longer durations build more energy
Squeeze Intensity: Percentage score of compression buildup
Squeeze Release: Transition from compression to expansion
Squeeze releases are among the most reliable volatility signals - they often precede significant price moves.
3. Historical Volatility Analysis
For additional confirmation, the indicator calculates statistical volatility:
f_historical_vol(int period, int annual_days) =>
float log_return = math.log(close / close )
float hv = ta.stdev(log_return, period) * math.sqrt(annual_days) * 100
hv
float hv_current = i_use_hv ? f_historical_vol(i_hv_len, i_hv_annual) : 0
float hv_avg = i_use_hv ? ta.sma(hv_current, i_hv_len * 2) : 0
float hv_ratio = hv_avg > 0 ? hv_current / hv_avg : 1.0
HV features:
Log Returns Calculation: Statistically sound volatility measurement
Annualization: Converts to annualized volatility percentage
HV Ratio: Current volatility relative to historical average
HV Regime: High/low volatility classification
Confirmation Layer: Validates ATR-based regime detection
Historical volatility adds a statistical layer that confirms what the ATR analysis is showing.
4. Volatility Regime Classification
The indicator classifies volatility into four distinct states:
// Raw regime based on ATR ratio
int raw_vol_regime = 0
if atr_ratio >= i_exp_thresh
raw_vol_regime := 1 // Expansion
else if atr_ratio <= i_con_thresh
raw_vol_regime := -1 // Contraction
// Confirmed regime with bar count filter
var int regime_counter = 0
var int confirmed_vol_regime = 0
if raw_vol_regime == raw_vol_regime and raw_vol_regime != 0
regime_counter := math.min(regime_counter + 1, i_regime_confirm + 1)
else if raw_vol_regime != raw_vol_regime
regime_counter := 1
if regime_counter >= i_regime_confirm
confirmed_vol_regime := raw_vol_regime
Regime types:
Expansion (ATR ratio > 1.4): High volatility, wide ranges, increased risk
Contraction (ATR ratio < 0.6): Low volatility, narrow ranges, preparing for breakouts
Normal (0.6 < ATR ratio < 1.4): Balanced volatility, normal market conditions
Transitioning: Regime changes requiring confirmation before acting
Regime confirmation prevents whipsaws by requiring multiple bars in the same regime before classification.
5. Volatility Cycle Phases
Beyond simple regimes, the indicator identifies where you are in the volatility cycle:
// Cycle phases: 0=neutral, 1=building, 2=peak, 3=declining, 4=trough
var int vol_cycle_phase = 0
float atr_slope = atr_slow - atr_slow
float atr_accel = atr_slope - nz(atr_slope )
if confirmed_vol_regime == 1
if atr_accel > 0
vol_cycle_phase := 1 // Building expansion
else
vol_cycle_phase := 2 // Peak expansion
else if confirmed_vol_regime == -1
if atr_accel < 0
vol_cycle_phase := 3 // Declining to contraction
else
vol_cycle_phase := 4 // Trough contraction
Cycle phases:
Building Expansion: Volatility increasing, acceleration positive
Peak Expansion: High volatility but decelerating
Declining to Contraction: Volatility decreasing rapidly
Trough Contraction: Low volatility stabilizing
Neutral: Transition periods between phases
Cycle analysis helps anticipate the next phase and prepare strategy adjustments.
6. Adaptive Multipliers
The indicator provides dynamic multipliers for risk management:
// Dynamic stop multiplier based on regime
float adaptive_stop_mult = switch confirmed_vol_regime
1 => 1.5 // Wider stops in expansion
-1 => 0.8 // Tighter stops in contraction
=> 1.0 // Normal
// Dynamic target multiplier
float adaptive_target_mult = switch confirmed_vol_regime
1 => 2.0 // Larger targets in expansion
-1 => 1.2 // Smaller targets in contraction
=> 1.5 // Normal
Adaptive features:
Stop Multiplier: Adjusts stop distance based on volatility regime
Target Multiplier: Scales profit targets to volatility conditions
Risk Adjustment: Helps maintain consistent risk across volatility regimes
Export Functions: Available for integration with trading systems
These multipliers help maintain consistent risk-to-reward ratios across different volatility environments.
Visual Elements
Multi-Layer Histogram: Core volatility ratio with gradient coloring
Glow Effects: Intensity-based glow around extreme volatility
Squeeze Momentum: Separate plot showing squeeze building/release
Cycle Momentum: Volatility cycle acceleration/deceleration
Background Shading: Regime-based background colors
Signal Markers: Premium volatility signals with labels
Dashboard: Real-time volatility metrics and forecasts
The dashboard displays:
1. Current volatility regime and strength
2. Cycle phase and momentum
3. ATR ratio and percentage
4. Percentile ranking of current volatility
5. Squeeze status and duration
6. Quality score of current setup
7. Volatility forecast (expansion/contraction)
8. Adaptive multipliers for risk management
Input Parameters
ATR Settings:
Fast ATR Period: Short-term volatility (default: 7)
Slow ATR Period: Medium-term volatility (default: 21)
Baseline Period: Long-term volatility average (default: 50)
Regime Thresholds:
Expansion Threshold: ATR ratio for expansion regime (default: 1.4)
Contraction Threshold: ATR ratio for contraction regime (default: 0.6)
Regime Confirmation: Bars for regime confirmation (default: 3)
Squeeze Detection:
Bollinger Period: BB calculation period (default: 20)
Bollinger Multiplier: BB standard deviation (default: 2.0)
Keltner Period: KC calculation period (default: 20)
Keltner Multiplier: KC ATR multiplier (default: 1.5)
Visual Settings:
Color Scheme: Customizable colors for each regime
Glow Effects: Enable/disable visual enhancements
Dashboard Display: Show/hide metrics panel
Signal Labels: Control signal label frequency
How to Use This Indicator
Step 1: Identify Current Regime
Check the dashboard for the current volatility regime. In expansion (red), expect larger ranges and adjust stops wider. In contraction (blue), prepare for potential breakouts. Normal conditions (purple) allow standard trading approaches.
Step 2: Monitor Squeeze Patterns
Watch for squeeze onset (compression) and duration. Longer squeezes (high intensity) often lead to more explosive releases. The squeeze release signal is one of the most reliable volatility breakout patterns.
Step 3: Analyze Cycle Phase
Understanding the cycle phase helps anticipate the next move. Building expansion suggests continued volatility, while peak expansion warns of potential contraction ahead.
Step 4: Use Percentile Context
The ATR percentile shows how current volatility compares to historical levels. Extremely high percentiles (>90) suggest mean reversion to lower volatility, while low percentiles (<10) suggest expansion is likely.
Step 5: Apply Adaptive Multipliers
Use the provided stop and target multipliers to adjust your risk management to current conditions. This maintains consistent risk across different volatility environments.
Step 6: Watch for Premium Signals
Premium expansion signals (squeeze release + high volatility + HV confirmation) offer high-probability breakout opportunities. Premium contraction signals (early contraction + low HV) suggest optimal entry points before breakouts.
Best Practices
Use the indicator to adapt your strategy to volatility conditions rather than fighting them
Squeeze releases are most reliable when they occur after long compression periods (>10 bars)
Volatility expansion often follows news events - be aware of economic calendars
In low volatility environments, reduce position size but increase stop distance proportionally
High volatility periods offer larger profit potential but require wider stops and smaller position sizes
The volatility forecast is mean-reversion based - extreme volatility tends to revert to normal
Combine with trend analysis for best results - volatility expansion in the direction of trend is powerful
Use the adaptive multipliers in your automated strategies for dynamic risk management
Monitor the cycle phase to anticipate regime changes before they occur
Keep a volatility journal to track how different instruments behave in various regimes
Strategy Integration
This indicator is designed to integrate seamlessly with other trading systems:
Export plots provide volatility data for strategy consumption
Adaptive multipliers can be imported for dynamic risk management
Regime classification can filter trades based on volatility conditions
Squeeze signals can trigger breakout strategies
Cycle analysis can optimize entry/exit timing
Quality scores can weight signal strength in composite systems
The indicator includes 12 export functions for integration:
ATR Ratio Export: Normalized volatility level
Vol Regime Export: Current regime classification (-1, 0, 1)
ATR Percentile Export: Historical volatility context
Adaptive ATR Export: Volatility-adjusted ATR value
Stop Multiplier Export: Dynamic stop adjustment factor
Target Multiplier Export: Dynamic target adjustment factor
Squeeze State Export: Binary squeeze on/off signal
Squeeze Momentum Export: Squeeze building/release momentum
Vol Score Export: Normalized volatility score (-100 to +100)
Technical Implementation
Built with Pine Script v6 featuring:
Multi-timeframe volatility analysis across three ATR periods
Statistical historical volatility calculation with log returns
Advanced squeeze detection with duration and intensity tracking
Regime classification with confirmation logic to prevent whipsaws
Cycle phase analysis using slope and acceleration
Adaptive multiplier system for dynamic risk management
Comprehensive visualization with multi-layer glow effects
Real-time dashboard with 11 key volatility metrics
Alert conditions for all major volatility events
Export functions for strategy integration
The code uses confirmed bars for all calculations to prevent repainting and ensure reliable signals.
Originality Statement
This indicator is original in its comprehensive approach to volatility analysis and regime classification. While individual components (ATR, Bollinger Bands, Keltner Channels) are established tools, this indicator is justified because:
It synthesizes multiple volatility measurement approaches into a unified framework
The regime classification system provides actionable market state information
Cycle phase analysis adds predictive capability beyond simple volatility measurement
The squeeze detection system includes duration and intensity scoring for signal quality
Adaptive multipliers provide practical risk management adjustments based on volatility
Historical volatility adds statistical confirmation to price-based volatility measures
The forecasting system uses mean reversion principles for volatility prediction
Comprehensive visualization makes complex volatility concepts accessible and actionable
Export functions enable integration with other trading systems
Each component contributes unique insights: ATR shows current volatility, squeeze shows compression, HV shows statistical volatility, cycles show direction, and multipliers provide practical application
The indicator's value lies in transforming volatility from a single number into a rich, multi-dimensional analysis that helps traders understand not just how volatile the market is, but where it is in the volatility cycle and what that means for trading opportunities.
Disclaimer
This indicator is provided for educational and informational purposes only. It is not financial advice or a recommendation to buy or sell any financial instrument. Volatility analysis is a tool for understanding market conditions, not a prediction system.
Volatility patterns can change suddenly due to market events, news, or changes in market structure. Past volatility patterns do not guarantee future behavior. The indicator's signals are mathematical calculations based on historical patterns and should be used in conjunction with other forms of analysis.
Always use proper risk management, including stop losses and position sizing appropriate for current volatility conditions. High volatility periods require smaller position sizes due to increased risk, while low volatility periods may require wider stops to avoid premature exits.
The author is not responsible for any losses incurred from using this indicator. Users assume full responsibility for all trading decisions made using this system.
-Made with passion by officialjackofalltrades
Indicator
Adaptive Volatility Matrix [JOAT]Adaptive Volatility Matrix
Introduction
The Adaptive Volatility Matrix (AVM) is an advanced open-source volatility regime classification indicator that combines Bollinger Band Width Percentile (BBWP), ATR percentile analysis, regime transition prediction, volatility clustering detection, and historical regime statistics to classify market conditions into distinct volatility regimes. This indicator helps traders adapt their strategies to current market conditions by systematically identifying when volatility is expanding, contracting, or transitioning between regimes.
Unlike basic volatility indicators that simply plot ATR or Bollinger Bands, AVM employs a sophisticated dual-metric system that combines BBWP (measuring price range compression/expansion) with ATR percentile (measuring absolute volatility) to create a combined volatility score (0-100%). The indicator then classifies this score into five distinct regimes and predicts regime transitions through momentum analysis.
Why This Indicator Exists
This indicator addresses the challenge of adapting trading strategies to volatility conditions. Different market regimes require different approaches - mean reversion works in low volatility, breakout strategies work in expansion, and risk management becomes critical in extreme volatility. AVM systematically reveals:
BBWP Analysis: Measures Bollinger Band width percentile to identify compression/expansion cycles
ATR Percentile: Tracks normalized ATR percentile to measure absolute volatility levels
Combined Volatility Score: Weighted average (60% BBWP, 40% ATR) for robust regime classification
Regime Classification: Five distinct regimes (Extreme Expansion, Expansion, Normal, Contraction, Extreme Contraction)
Transition Prediction: Momentum-based forecasting of next regime with probability
Volatility Clustering: Detects sustained high/low volatility periods
Historical Statistics: Tracks regime duration and frequency for context
Each component provides unique intelligence. BBWP shows compression cycles, ATR shows absolute volatility, combined score provides robust classification, regime system categorizes conditions, transition prediction anticipates changes, clustering detects persistence, and statistics provide historical context.
Core Components Explained
1. BBWP (Bollinger Band Width Percentile) Calculation
BBWP measures where current Bollinger Band width ranks relative to historical width:
f_calculate_bbwp(int length, int lookback) =>
float basis = ta.sma(close, length)
float dev = ta.stdev(close, length)
float bb_width = (dev * 2) / basis * 100
// Calculate percentile rank
int count = 0
for i = 1 to lookback
if bb_width > nz(bb_width )
count += 1
float bbwp = (count / lookback) * 100
BBWP ranges from 0-100%:
- 0-20%: Extreme compression (volatility squeeze)
- 20-40%: Contraction (below average volatility)
- 40-60%: Normal (average volatility)
- 60-80%: Expansion (above average volatility)
- 80-100%: Extreme expansion (volatility breakout)
2. ATR Percentile Analysis
ATR percentile measures where current normalized ATR ranks historically:
f_atr_percentile(int period, int lookback) =>
float atr_val = ta.atr(period)
float natr = close > 0 ? (atr_val / close) * 100 : 0.0
float percentile = ta.percentrank(natr, lookback)
Normalized ATR (NATR) accounts for price level differences, making volatility comparable across different price ranges. Percentile ranking shows where current volatility sits in historical distribution.
3. Combined Volatility Score & Regime Classification
The combined score weights BBWP more heavily than ATR percentile:
float combined_score = (bbwp_value * 0.6) + (atr_percentile * 0.4)
f_classify_regime(float bbwp_val, float atr_perc, float exp_th, float con_th, float ext_th) =>
string regime = "Normal"
int regime_code = 0
if bbwp_val >= ext_th or atr_perc >= ext_th
regime := "Extreme Expansion"
regime_code := 4
else if bbwp_val >= exp_th or atr_perc >= exp_th
regime := "Expansion"
regime_code := 3
// Additional classifications...
Five regime classifications:
1. Extreme Contraction (code 1): Both metrics <30%, volatility squeeze
2. Contraction (code 2): One metric <40%, below average volatility
3. Normal (code 0): Both metrics 40-60%, average conditions
4. Expansion (code 3): One metric >70%, above average volatility
5. Extreme Expansion (code 4): Both metrics >85%, volatility breakout
4. Regime Transition Prediction
AVM predicts next regime through momentum analysis:
float regime_momentum = combined_score - combined_score
string momentum_direction = regime_momentum > 2 ? "Accelerating" :
regime_momentum < -2 ? "Decelerating" : "Stable"
string predicted_regime = regime_code == 4 and regime_momentum < -5 ? "→ Expansion" :
regime_code == 3 and regime_momentum < -3 ? "→ Normal" :
// Additional predictions...
"Stable"
float transition_prob = math.min(math.abs(regime_momentum) * 10, 100)
Transition probability (0-100%) based on momentum magnitude. >50% probability triggers warning.
5. Volatility Clustering Detection
Clustering identifies sustained high/low volatility periods:
int cluster_lookback = 20
float cluster_threshold = 70.0
int high_vol_count = 0
for i = 0 to cluster_lookback - 1
if combined_score >= cluster_threshold
high_vol_count += 1
float cluster_ratio = high_vol_count / cluster_lookback * 100
bool in_vol_cluster = cluster_ratio >= 60 // 60% of bars are high vol
string cluster_strength = cluster_ratio >= 80 ? "Strong" :
cluster_ratio >= 60 ? "Moderate" :
cluster_ratio >= 40 ? "Weak" : "None"
Clusters indicate persistent volatility conditions that tend to continue.
6. Historical Regime Statistics
AVM tracks regime history for context:
var array regime_history = array.new_int(0)
var array regime_durations = array.new_int(0)
if regime_changed
array.push(regime_history, regime_code)
array.push(regime_durations, bars_in_regime)
// Calculate statistics
float avg_expansion_duration = exp_sum / exp_cnt
float avg_contraction_duration = con_sum / con_cnt
float duration_ratio = bars_in_regime / avg_expansion_duration
bool regime_extended = duration_ratio > 1.5
Statistics show if current regime is extended (>1.5x average duration), suggesting potential transition.
Visual Elements
Combined Score Line: Main plot (0-100%) with regime-based coloring
ATR Percentile Overlay: Circles showing ATR percentile for comparison
Histogram: Gradient-colored bars showing volatility score with regime colors
Reference Lines: 70% (expansion), 50% (neutral), 30% (contraction), 85% (extreme)
Background Zones: Regime-colored backgrounds (purple for expansion, yellow for contraction)
Transition Warnings: ⚠ symbols when transition probability >50%
BBWP Percentile Bands: 20th, 50th, 80th percentile circles for context
Dashboard: Real-time metrics including regime, score, BBWP, ATR%, trend, duration, momentum, transition prediction, cluster status, duration ratio, historical stats
Input Parameters
BBWP Parameters:
BBWP Length: Bollinger Band period (default: 13)
BBWP Lookback: Historical comparison period (default: 252)
ATR Analysis:
ATR Period: ATR calculation period (default: 14)
ATR Percentile Lookback: Historical ranking period (default: 100)
Regime Classification:
Expansion Threshold: Score for expansion regime (default: 70%)
Contraction Threshold: Score for contraction regime (default: 30%)
Extreme Threshold: Score for extreme regimes (default: 85%)
Visualization:
Show Regime Zones: Toggle background coloring
Show Histogram: Toggle volatility histogram
Show ATR Overlay: Toggle ATR percentile circles
How to Use This Indicator
Step 1: Identify Current Regime
Check dashboard "Regime" row. Adjust strategy based on classification.
Step 2: Monitor Combined Score
Score >70% = expansion (use breakout strategies)
Score <30% = contraction (use mean reversion)
Score 40-60% = normal (use balanced approach)
Step 3: Check Momentum Direction
"Accelerating" = volatility increasing
"Decelerating" = volatility decreasing
"Stable" = no significant change
Step 4: Watch for Transition Warnings
⚠ symbols indicate >50% probability of regime change. Prepare to adjust strategy.
Step 5: Assess Cluster Status
"Strong" or "Moderate" cluster = persistent conditions likely to continue
Step 6: Consider Duration Ratio
Ratio >1.5x = extended regime, higher probability of mean reversion
Best Practices
Use regime classification to select appropriate trading strategies
Extreme contraction often precedes volatility breakouts - prepare for expansion
Extreme expansion often mean-reverts - reduce position sizes
Transition warnings provide early signal to adjust risk management
Volatility clusters suggest persistence - don't fight the regime
Extended regimes (>1.5x average) have higher reversal probability
BBWP and ATR percentile divergence suggests regime uncertainty
Historical statistics provide context for current regime duration
Combine with directional indicators - AVM shows conditions, not direction
Indicator Limitations
Regime classification is backward-looking - transitions lag actual changes
BBWP calculation is computationally intensive on large lookback periods
Transition predictions are probabilistic, not deterministic
Extreme regimes can persist longer than expected during major events
Historical statistics require sufficient data (50+ regime changes)
Clustering detection has fixed lookback - may miss longer-term patterns
Combined score weighting (60/40) may not be optimal for all instruments
Regime thresholds may need adjustment for different markets
Technical Implementation
Built with Pine Script v6 using:
Custom BBWP calculation with percentile ranking
ATR percentile analysis with normalized ATR
Weighted combined score (60% BBWP, 40% ATR)
Five-tier regime classification system
Momentum-based transition prediction with probability
Volatility clustering detection (20-bar lookback)
Historical regime tracking with arrays (last 50 regimes)
Duration ratio calculation vs historical averages
BBWP percentile bands (20th, 50th, 80th)
Adaptive background coloring based on regime and duration
Comprehensive dashboard with 12 metrics
The code is fully open-source and can be modified to suit individual trading styles.
Originality Statement
This indicator is original in its comprehensive volatility regime classification approach. While BBWP and ATR are established concepts, this indicator is justified because:
It combines BBWP and ATR percentile into weighted combined score for robust classification
The five-tier regime system provides granular volatility categorization
Momentum-based transition prediction with probability quantification is unique
Volatility clustering detection identifies persistent regime conditions
Historical regime statistics provide context for current regime duration
Duration ratio calculation identifies extended regimes with mean reversion potential
BBWP percentile bands add additional context layers
Adaptive background intensity based on regime stability
Each component contributes unique information: BBWP shows compression cycles, ATR shows absolute volatility, combined score provides robust classification, regime system categorizes conditions, transition prediction anticipates changes, clustering detects persistence, statistics provide context, and duration ratio identifies extremes. The indicator's value lies in presenting these complementary perspectives simultaneously with unified regime framework.
Disclaimer
This indicator is provided for educational and informational purposes only. It is not financial advice. Regime classifications do not guarantee future volatility behavior. Trading involves substantial risk of loss. Past performance does not guarantee future results. Always use proper risk management and never risk more than you can afford to lose.
-Made with passion by officialjackofalltrades Indicator
Volatility Regime Switch [Metrify]VRS is a regime classifier that tries to separate two things most indicators mix together: direction and tradability. It doesn’t just ask "is price above/below a line?". it estimates whether the market is currently behaving more like a trend regime or a noise/chop regime, then adapts its switching logic and trailing structure accordingly. The output is a state machine (bull/bear) with a volatility-normalized corridor, plus explicit markers for switch accepted vs switch rejected.
Core idea: switching should depend on regime
Most trend flip tools fail in choppy markets because they apply the same confirmation rules everywhere. VRS tries to avoid that by measuring a continuous regime score:
trreg ≈ how “trend-like” conditions are
nsreg ≈ how “noise-like” conditions are
That regime estimate is then used to:
shape the trailing band distance (wider in chop, tighter in trend),
change the required confirmation for a switch (more strict in noise), and
demand follow-through after a candidate switch (acceptance check).
Regime estimation: how it decides “trend-like” vs “noise-like”
The regime score is built from three normalized features, then blended using inverse-variance weighting again:
Efficiency ratio (ER): Measures directional efficiency: net displacement over a horizon vs total movement. Trends have higher efficiency; chop has lower.
ADX-like trend strength: A custom ADX calculation is normalized (adxn), giving a bounded “trend strength” component.
Volatility ratio (fast/slow): Compares fast ATR to slow ATR and normalizes it. This helps distinguish active expansion vs quieter conditions.
These three components are combined into trreg (0..1). Noise regime is nsreg = 1 - trreg.
The important part is it can behave differently when the market is structurally trending versus when it is structurally noisy.
The anchor + adaptive bands: how the corridor is built
VRS uses two EMAs:
a fast EMA (emaf)
a slower EMA (emas)
It then creates an anchor that interpolates between them based on regime:
when trend regime is strong (trreg high), the anchor leans toward the fast EMA (more responsive)
when noise regime is strong (nsreg high), it leans toward the slow EMA (more stable)
Band distance is bdist = volc * bmult, and bmult is also regime-dependent:
in noise, bmult becomes larger → bands widen → fewer false flips
in trend, bmult tightens → better trailing sensitivity
Finally, the trailing bands (fup, flo) use a classic "non-decreasing band" logic similar to trailing-stop structures: the band only moves in the favorable direction unless price invalidates it, preventing constant band oscillation.
Bias and conviction layer
A switch is not triggered merely by close above/below a band. VRS computes conviction, which mixes:
Intra-bar price action bias
Two normalized elements are used: CLV (close location value) inside the candle range and body direction/strength relative to candle range. Both are Z-scored and squashed (atan-based) to avoid extreme outliers dominating.
Trend bias
Difference between fast and slow EMA, normalized by volatility, then Z-scored and squashed.
Displacement breakout quality
If price breaks above fup or below flo, it computes a breakout 'distance' normalized by volatility, then converts it into a Z-score relative to recent breakout behavior (dbullz, dbearz)
These get blended into a conviction signal that is smoothed, and then compared against a dynamic trigger threshold built from the average + stdev of conviction magnitude. A flip should happen when price action + trend bias + breakout quality jointly exceed what is normal for this market recently.
Practical reading notes
VRS generally behaves best when read as "current regime context + boundary + switch events" rather than as a constant entry/exit engine. In trending conditions, the trail will tend to hug price more tightly and switches will be less frequent. In noisy conditions, the corridor widens and the script becomes more conservative, often producing rejected switch attempts rather than rapid flips.
The rejected-switch markers (yellow X) are explicit evidence that the script detected an attempted regime change but did not see enough acceptance. For discretionary use, those rejection points can be useful as information about failed break attempts or lack of follow-through.
This script is designed to be adaptive, but it still has structural constraints. It uses volatility normalization and regime weighting to reduce parameter brittleness, yet extreme regime changes (sudden volatility spikes, news-driven moves, illiquid gaps) can still cause behavior that looks late or 'overly strict', because acceptance and confirmation are intentionally conservative in high-noise conditions. Conversely, on very smooth trend legs, the trail can appear tight and switches may look clean, but that depends on how the chosen lengths match the instrument’s tempo.
Also, because this is a state machine with acceptance logic, you should expect situations where price briefly breaks a boundary and then returns—those are exactly the environments that produce rejected switches. The indicator surfaces that behavior explicitly instead of hiding it. Indicator
Vortex Volatility Engine [Pineify]Vortex Volatility Engine: Advanced Directional Volatility Momentum Indicator with Squeeze Detection
The Vortex Volatility Engine is a sophisticated momentum oscillator that combines directional volatility analysis with squeeze detection to identify high-probability trading opportunities. Unlike traditional volatility indicators that simply measure price dispersion, this indicator decomposes volatility into bullish and bearish components, revealing the underlying directional strength of market movements. By integrating True Range normalization, directional momentum filtering, and dynamic volatility bands, it provides traders with a comprehensive framework for detecting volatility compression periods (squeezes) and subsequent explosive breakout signals.
Key Features
Directional Volatility Decomposition: Separates upward and downward price movements into distinct volatility components, revealing which side of the market controls momentum.
Squeeze Detection System: Identifies low-volatility consolidation periods by comparing short-term True Range against long-term baselines, signaling potential setup phases for major moves.
Dynamic Volatility Bands: Adaptive upper and lower bands calculated using standard deviation, creating context-aware thresholds that adjust to changing market conditions.
Breakout Signal Generation: Automated detection of volatility expansion events when the delta crosses outside dynamic bands during non-squeeze periods.
Four-Color Momentum Gradient: Visual differentiation between strong/weak bullish and bearish momentum using bright and dim color coding.
Comprehensive Alert System: Real-time notifications for bullish breakouts, bearish breakouts, squeeze initiation, and squeeze release events.
How It Works
The Vortex Volatility Engine employs a multi-stage calculation methodology that transforms raw price data into actionable volatility intelligence:
Stage 1: True Range Baseline Calculation
The indicator begins by calculating a smoothed True Range using the Running Moving Average (RMA) method over the user-defined lookback period (default 14 bars). True Range captures the maximum of three values: current high-low range, absolute value of high minus previous close, and absolute value of low minus previous close. This provides a comprehensive measure of actual market volatility that accounts for gaps and limit moves.
Stage 2: Directional Volatility Separation
Price changes are decomposed into two distinct components:
Upward Volatility (up_vol): Captures only positive price changes using math.max(ta.change(close), 0), then smooths with RMA to create an average upward momentum measure.
Downward Volatility (dn_vol): Captures only negative price changes (converted to positive values) using math.max(-ta.change(close), 0), then smooths with RMA to create an average downward momentum measure.
Stage 3: Power Normalization
Both directional volatility components are normalized against the True Range baseline and converted to a 0-100 scale:
Bull Power = (up_vol / tr_smooth) × 100
Bear Power = (dn_vol / tr_smooth) × 100
This normalization ensures that the indicator adapts to different volatility regimes and instruments. Values above 50 indicate bullish dominance, while values below 50 indicate bearish dominance.
Stage 4: Vortex Delta Calculation
The core signal is derived by subtracting Bear Power from Bull Power, creating the Vortex Delta. This delta is then smoothed using a Simple Moving Average (default 5 periods) to reduce noise and prevent false signals. Positive delta values indicate bullish volatility dominance, while negative values indicate bearish dominance.
Stage 5: Squeeze Detection Logic
The indicator compares short-term True Range (using the primary length parameter) against a long-term True Range baseline (3× the primary length). When short-term volatility falls below a user-defined threshold (default 0.8× the long-term average), a squeeze condition is triggered. This identifies consolidation periods where the market is "coiling" before a potential explosive move.
Stage 6: Dynamic Band Construction
Upper and lower volatility bands are constructed using:
Basis Line: SMA of the Vortex Delta over 2× the primary length
Standard Deviation: Calculated over the same period
Upper Band: Basis + (StdDev × Band Multiplier)
Lower Band: Basis - (StdDev × Band Multiplier)
These bands create adaptive thresholds that expand during high-volatility periods and contract during low-volatility periods, providing context-aware breakout detection.
Trading Ideas and Insights
Breakout Trading Strategy
The primary trading methodology involves waiting for squeeze periods followed by volatility expansion breakouts:
Identify Squeeze: Watch for gray dots appearing on the zero line, indicating volatility compression.
Wait for Release: Monitor for the squeeze to fire (gray dots disappear), signaling the end of consolidation.
Confirm Direction: Enter trades when the Vortex Delta crosses above the upper band (bullish breakout) or below the lower band (bearish breakout) during non-squeeze periods.
Momentum Confirmation: Prioritize trades where the histogram shows bright colors (strong momentum) rather than dim colors (weak momentum).
Trend Continuation Signals
Use the histogram color gradient to identify trend strength:
Bright green bars (delta > 0 and increasing) suggest strong bullish momentum continuation
Dark green bars (delta > 0 but decreasing) suggest weakening bullish momentum, potential reversal warning
Bright red bars (delta < 0 and decreasing) suggest strong bearish momentum continuation
Dark red bars (delta < 0 but increasing) suggest weakening bearish momentum, potential reversal warning
Mean Reversion Opportunities
When the Vortex Delta reaches extreme levels outside the dynamic bands but fails to sustain momentum (color shifts from bright to dim), this can signal exhaustion and potential mean reversion back toward the zero line or basis.
How Multiple Indicators Work Together
The Vortex Volatility Engine integrates four distinct analytical components into a unified framework:
1. True Range Foundation
Provides the volatility baseline that normalizes all other calculations, ensuring the indicator adapts to different market conditions and instruments without requiring recalibration.
2. Directional Momentum Decomposition
By separating upward and downward price movements, the indicator reveals which side controls the market. This is superior to simple momentum oscillators that only show net movement, as it exposes the underlying battle between bulls and bears.
3. Squeeze Detection System
The squeeze component acts as a filter and setup identifier. By comparing short-term versus long-term volatility, it identifies periods of compression that historically precede significant directional moves. This prevents traders from taking breakout signals during normal volatility fluctuations.
4. Dynamic Volatility Bands
The standard deviation-based bands provide context-aware thresholds that adapt to changing market regimes. During high-volatility periods, the bands widen to prevent false signals. During low-volatility periods, they contract to capture smaller but significant moves.
Synergistic Integration:
These components work together in a logical sequence: True Range establishes the baseline → Directional decomposition reveals momentum → Squeeze detection identifies setup periods → Dynamic bands define breakout thresholds. Each component enhances the others, creating a robust system that filters noise while capturing genuine volatility expansion events.
Unique Aspects
Volatility Normalization Method: Unlike standard vortex indicators that use absolute price differences, this engine normalizes directional movements against True Range, creating a percentage-based power metric that works across all timeframes and instruments.
Four-Tier Color Coding: The histogram uses a sophisticated color gradient that distinguishes not just direction (bullish/bearish) but also momentum strength (accelerating/decelerating), providing instant visual feedback on trend quality.
Squeeze Filtering Logic: Breakout signals are only generated during non-squeeze periods, preventing false signals during consolidation and ensuring traders only act on genuine volatility expansion events.
Dual Smoothing Approach: Applies RMA smoothing to directional components and SMA smoothing to the final delta, balancing responsiveness with noise reduction.
Multi-Timeframe Volatility Analysis: Uses different lookback periods for squeeze detection (3× primary length) versus band calculation (2× primary length), creating a hierarchical volatility framework.
How to Use
Adding to Your Chart
Add the Vortex Volatility Engine to your chart - it displays in a separate pane below price.
The histogram shows the Vortex Delta (bullish/bearish volatility balance).
Gray circular dots on the upper and lower edges represent dynamic volatility bands.
Gray dots on the zero line indicate squeeze periods (low volatility compression).
Small colored circles on the histogram mark breakout signals.
Interpreting Signals
Histogram Above Zero: Bullish volatility dominance - upward price movements are stronger than downward movements.
Histogram Below Zero: Bearish volatility dominance - downward price movements are stronger than upward movements.
Bright Green Bars: Strong bullish momentum (delta positive and increasing) - trend continuation likely.
Dark Green Bars: Weak bullish momentum (delta positive but decreasing) - potential reversal warning.
Bright Red Bars: Strong bearish momentum (delta negative and decreasing) - downtrend continuation likely.
Dark Red Bars: Weak bearish momentum (delta negative but increasing) - potential reversal warning.
Squeeze Dots Present: Market in consolidation, volatility compressed - prepare for potential breakout.
Bullish Breakout Signal: Delta crosses above upper band during non-squeeze - enter long positions.
Bearish Breakout Signal: Delta crosses below lower band during non-squeeze - enter short positions.
Setting Up Alerts
Right-click on the indicator and select "Add Alert"
Choose from four alert conditions: Bullish Vortex Breakout, Bearish Vortex Breakout, Squeeze Started, Squeeze Fired
Configure notification preferences (popup, email, webhook, etc.)
Alerts will trigger automatically when conditions are met, allowing hands-free monitoring
Customization
Volatility Length (Default: 14)
Controls the lookback period for True Range and directional momentum calculations. Lower values (8-10) create a more responsive indicator suitable for intraday trading and volatile markets. Higher values (20-30) produce smoother signals better suited for swing trading and trending markets. Adjust based on your trading timeframe and market conditions.
Signal Smoothing (Default: 5)
Applies final smoothing to the Vortex Delta histogram to reduce noise and prevent whipsaws. Lower values (2-3) maintain responsiveness but may generate more false signals. Higher values (7-10) create cleaner signals but with increased lag. Use lower smoothing for scalping, higher smoothing for position trading.
Squeeze Threshold (Default: 0.8)
Determines how strict the squeeze detection is. Lower values (0.6-0.7) require more significant volatility compression, resulting in fewer but higher-quality squeeze signals. Higher values (0.9-1.0) detect squeezes more frequently but may include less significant consolidations. Adjust based on your preferred trade frequency.
Volatility Band Multiplier (Default: 2.0)
Controls the width of the dynamic volatility bands. Lower values (1.5-1.8) create tighter bands that generate more frequent breakout signals but with higher false positive rates. Higher values (2.5-3.0) create wider bands that filter out noise but may miss smaller breakout opportunities. Optimize based on backtesting results for your specific instrument and timeframe.
Recommended Settings by Trading Style
Scalping (1-5 min charts): Length: 8, Smoothing: 3, Squeeze: 0.7, Bands: 1.8
Day Trading (15-60 min charts): Length: 14, Smoothing: 5, Squeeze: 0.8, Bands: 2.0
Swing Trading (4H-Daily charts): Length: 21, Smoothing: 7, Squeeze: 0.85, Bands: 2.5
Conclusion
The Vortex Volatility Engine represents a comprehensive approach to volatility-based momentum trading by combining directional decomposition, squeeze detection, and adaptive band analysis into a single, cohesive framework. By normalizing volatility components against True Range and implementing multi-stage filtering logic, it provides traders with high-probability setup identification and breakout confirmation signals. Whether you're trading breakouts from consolidation, following momentum trends, or identifying exhaustion reversals, this indicator delivers the volatility intelligence needed to make informed trading decisions across all timeframes and market conditions. Indicator
ADR**Overview**
This indicator displays the **Average Daily Range (ADR)** and **ADR Percentage** in a customizable table on your chart.
While the standard ATR (Average True Range) is a popular metric for volatility, it accounts for price gaps (e.g., overnight moves). **ADR**, on the other hand, strictly measures the average distance between the **High** and **Low** of price bars, completely ignoring gaps.
**Why use ADR instead of ATR?**
* **Day Trading:** For intraday traders (Forex, Crypto, Futures), ADR is often preferred because it calculates the "tradable" range of the day. It answers the question: *"On average, how much does this asset move from High to Low?"*
* **Target Setting:** ADR is excellent for projecting daily highs and lows. If price has already moved 100% of its ADR, the statistical probability of further extension decreases.
* **Pure Volatility:** It filters out the noise of overnight gaps to show pure intraday volatility.
**Calculation Logic**
* **ADR:** Calculated using a Simple Moving Average (SMA) of the `High - Low` range over the specified length.
* Formula: `SMA(High - Low, Length)`
* **ADR%:** Shows the ADR relative to the current price.
* Formula: `(ADR / Current Close) * 100`
**Features**
* **Clean Dashboard:** A minimalist table displays the ADR value and the ADR %.
* **Customizable:** You can change the calculation length (default is 14) and move the table to any corner of the chart (Top/Bottom, Left/Right) to fit your workspace.
**Settings**
* **ADR Length:** The lookback period for the average (Default: 14).
* **Display Position:** Choose where the table appears on your screen. Indicator
BE-QuantFlow: Adaptive Momentum Trading█ Overview: QuantFlow: Adaptive Momentum Trading
QuantFlow is a sophisticated algorithmic momentum trading method designed specifically for indices and high-beta stocks. However, its logic is universal; with appropriate parameter tuning, it adapts to various asset classes and timeframes.
While the standard momentum indicators (like RSI or MACD) simply measure how fast price is moving (Velocity), QuantFlow analyzes the quality and conviction of the trend . Features like Dynamic Volatility Filtering and Trend Shielding, combined with volatility weighting and a "Dual-Line" approach to distinguish between a sustainable institutional trend and a temporary retail spike, make the indicator unique and more powerful.
█ Why QuantFlow ?
Quant (The Engine): This replaces subjective guessing with objective math.
Instead of just seeing that the price is "up," we measure "how it got there". For example, a stock that rises 1 currency value every day for 10 days (smooth trend) gets a much higher score than a stock that jumps 10 currency value in one minute and does nothing else (erratic noise). This mathematical rigor provides the structure.
█ Core Logic & Philosophy
To understand how QuantFlow calculates momentum, imagine a "Tug-of-War" between Buyers (Bulls) and Sellers (Bears). Most indicators (like RSI) use a single line. If RSI is at 50, it means "Neutral." But "Neutral" can mean two very different things:
Peace: Nothing is happening. No one is buying or selling.
War: Buyers are pushing hard, but Sellers are pushing back equally hard. Volatility is massive.
A single line hides this reality. QuantFlow splits the market into two separate scores:
Bull Score (Green Line): How hard are the buyers pushing?
Bear Score (Red Line): How hard are the sellers pushing?
The Layman's Advantage:
If both lines are low = Sleepy Market (Avoid).
If Green is high and Red is low = Clean Uptrend (Buy).
If Red is high and Green is low = Clean Downtrend (Sell).
If both lines are high = Chaos/War Zone (Wait).
█ How it Weight "Sustenance" (The Critical Quality Check)
This is the most unique aspect of QuantFlow: Trend direction alone is not enough; Sustenance is weighed equally . Standard indicators treat every 10 currency value movements the same way with no distinction. However, QuantFlow asks, "Did you hold the ground you gained?"
Scenario A (High Sustenance) : A stock opens at 100, marches to 110, and closes at 110.
Verdict : Buyers pushed up and sustained the price.
QuantFlow Weight : 100%. This is a high-quality move.
Scenario B (Low Sustenance) : A stock opens at 100, spikes to 110, but gets sold off to close at 102.
Verdict : Buyers pushed up (Trend is Up), but failed to sustain it (Long Wick).
QuantFlow Weight : 20%. This is treated as "Noise" or a trap.
By mathematically weighing the Close Location Value (where the candle closes relative to its high/low), QuantFlow filters out "Gap-and-Fade" traps and exhaustion spikes that fool traditional indicators.
Comparisons: QuantFlow vs. The Rest
Calculation Logic : Standard RSI/MACD measures simple price change over time. QuantFlow measures Price Change 'times (x)' Conviction (Sustenance Weighting).
Visual Output : Standard tools show a single line (0-100), often hiding market conflict. QuantFlow displays Dual Lines (Bull vs Bear Intensity) to reveal the true state of the battle.
Trap Handling : Standard indicators are often fooled by sharp spikes. QuantFlow ignores "Gap-and-Fade" moves with poor closing conviction.
Adaptability : Standard tools use static levels (e.g., Overbought > 70). QuantFlow uses Dynamic Bands that adjust automatically to recent volatility.
█ Dynamic Volatility Filtering
Unlike standard indicators that use fixed levels (e.g., "Buy if RSI > 50"), QuantFlow acknowledges that "50" means something different in a quiet market versus a crashing market. This section explains the statistical engine driving the signals.
The Problem with Static Levels : In a low-volatility environment, a momentum score of 55 might indicate a massive breakout. In a high-volatility environment, a score of 55 might just be random noise. A fixed threshold cannot handle both scenarios.
The Solution: Adaptive Statistics : The script maintains a memory of the Momentum Events. It doesn't just look at price; it looks at where the momentum occurred in the past and draws a "Noise Zone" (Grey Band). This logic acts as a "Smart Gatekeeper" for trade entries:
Scenario A: Inside the Noise (The Filter)
If a new momentum signal happens inside the Noise Zone, the script assumes it is likely chop or noise.
Action : It forces a wait period. The signal is delayed until the trend sustains itself for Confirm Bars; else the signal is cancelled. This filters out ~70% of false signals in sideways markets.
Scenario B: Outside the Noise (The Breakout)
If a new momentum signal happens outside the Noise Zone (or the momentum score smashes through the Upper Band), it is statistically significant (an outlier event).
Action: It triggers an Immediate Entry. No waiting is required because the move is powerful enough to escape the historical noise zone.
█ The ⚠️ "Warning" System (Heads-up for Smart Reversals)
While you are directional if there is potential reversal signal, it provides the heads-up warning for a better decision-making
█ Special Utility: Ghost Mode
For intraday traders, the biggest disruption to "Flow" is the mandatory broker square-off at 3:15 PM (considering Indian Market). Often, a trend continues overnight, and the trader misses the gap-up opening the next morning because their algo was flat.
Ghost Mode is a unique feature that runs silently in the background:
At Square-off: The strategy closes your official position to satisfy the broker.
In the Background: It keeps the trade "alive" virtually (Ghost).
Next Morning: If the market opens in the trend's favor, the strategy re-enters the trade automatically. This approach ensures you capture the full swing of the trend, even if you are forced to exit at the previous session.
█ Advice on this indicator:
Parameter Calibration: The default settings are optimized for BankNifty on 5-minute charts. If you trade stocks, crypto, commodities, or any higher timeframes (e.g., 15-min or hourly), you must adjust these.
Low Volatility Assets: Reduce Stop Multiplier to 2.0.
High Volatility Assets: Increase Momentum Lookback to 50 to filter noise.
Confluence (Additional Confirmation): While QuantFlow is a complete system, using it alongside Key Support/Resistance Levels or Volume Profile provides the highest probability setups. Strategy
GARCH Volume Volatility [MarkitTick]Title: GARCH Volume Volatility
Description
Overview
The GARCH Volume Volatility (GV) indicator is a sophisticated quantitative tool designed to analyze the rate of change in market participation. While the vast majority of technical indicators focus on Price Volatility (how much price moves), this script focuses on Volume Volatility (how unstable the participation is).
Market volume is rarely distributed evenly; it tends to cluster. Periods of high activity are often followed by more high activity, and periods of calm tend to persist. This behavior is known as "heteroskedasticity." This script utilizes an Exponentially Weighted Moving Average (EWMA) model—a core component of Generalized Autoregressive Conditional Heteroskedasticity (GARCH) frameworks—to model these changing variance regimes.
By isolating volume volatility from raw volume data, this tool helps traders distinguish between sustainable liquidity flows and erratic, unsustainable volume shocks that often precede market reversals or breakouts.
Methodology and Calculations
1. Logarithmic vs. Percentage Returns
The foundation of this indicator is the calculation of "Volume Returns"—the period-over-period change in volume.
- The script defaults to Logarithmic Returns. In financial statistics, log returns are preferred because they normalize data that can vary wildly in magnitude (such as cryptocurrency volume spikes), providing a more symmetric view of changes.
- Users can opt for standard percentage changes if they prefer a linear approach.
2. Variance Proxy (Squared Returns)
To measure volatility, the direction of the volume change (up or down) matters less than the magnitude. The script squares the returns to create a "Variance Proxy." This ensures that a massive drop in volume is treated with the same statistical weight as a massive spike in volume—both represent a significant change in the volatility of participation.
3. GARCH-Style Smoothing (EWMA)
Standard Moving Averages (SMA) treat all data points in the lookback period equally. However, volatility is dynamic. This script uses an EWMA model with a tunable "Lambda" (Decay Factor).
- The Recursive Formula: The current calculation relies on a weighted average of the current variance and the previous period's smoothed variance.
- Memory Effect: This allows the indicator to "remember" recent volatility shocks while gradually letting their influence fade. This mimics the GARCH process of conditional variance.
4. Dynamic Statistical Thresholds
The final output is the Volatility (square root of variance). To make this data actionable, the script calculates a dynamic upper and lower limit based on the standard deviation (Z-Score) of the volatility itself over a user-defined lookback period.
How to Use
The indicator plots a histogram that categorizes the market into four distinct volatility regimes:
1. High Volatility (Red Histogram)
Trigger: Volatility > High Band (Upper Standard Deviation).
Interpretation: This signals an extreme anomaly in volume stability. This is not just "high volume," but "erratic volume behavior." This often occurs at:
- Capitulation bottoms (panic selling).
- Euphoric tops (blow-off tops).
- Major news events or earnings releases.
2. Elevated Volatility (Maroon Histogram)
Trigger: Volatility > Mean Average.
Interpretation: The market is in an active state. Participation is changing rapidly, but within statistically normal bounds. This is common during healthy, trending moves where new participants are entering the market steadily.
3. Normal/Low Volatility (Green Histogram)
Trigger: Volatility is within the lower bands.
Interpretation: The market volume is stable. There are no sudden shocks in participation. This is typical of consolidation phases or "creeping" trends where the price drifts without significant volume conviction.
4. Extremely Low Volatility (Bright Green/Transparent)
Trigger: Volatility < Low Band.
Interpretation: The "calm before the storm." When volume volatility collapses to near-zero, it implies that the market has reached a state of equilibrium or disinterest. Historically, volatility is cyclical; periods of extreme compression often lead to violent expansion.
Settings and Configuration
Core Settings
- Use EWMA: When checked (Default), uses the recursive GARCH-style calculation. If unchecked, it reverts to a simple SMA of variance, which is less sensitive to recent shocks but more stable.
- Log Returns: Uses natural log for calculations. Highly recommended for assets with exponential growth or large volume ranges.
- Length: The baseline period for the calculation.
- Threshold Lookback: The number of bars used to calculate the Mean and Standard Deviation bands.
- EWMA Lambda: The decay factor (0.0 to 1.0). A value of 0.94 is standard for risk metrics.
-- Higher Lambda (e.g., 0.98): The indicator reacts slower and is smoother (long memory).
-- Lower Lambda (e.g., 0.80): The indicator reacts very fast to new data (short memory).
Visuals
- Show Thresholds: Toggles the visibility of the statistical bands on the chart.
- High Band (StdDev): The multiplier for the upper warning zone. Default is 1.5 deviations. Increasing this to 2.0 or 3.0 will filter for only the most extreme events.
Disclaimer This tool is for educational and technical analysis purposes only. Breakouts can fail (fake-outs), and past geometric patterns do not guarantee future price action. Always manage risk and use this tool in conjunction with other forms of analysis. Indicator
Strategy
Indicator
ADR Plots + OverlayADR Plots + Overlay
This tool calculates and displays Average Daily Range (ADR) levels on your chart, giving traders a quick visual reference for expected daily price movement. It plots guide levels above and below the daily open and shows how much of the day's typical range has already been covered—all in one interactive table and on-chart overlay.
What It Does
ADR Calculation:
Uses daily high-low differences over a user-defined period (default 14 days), smoothed via RMA, SMA, EMA, or WMA to calculate the average daily range.
Projected Levels:
Plots four reference levels relative to the current day's open price:
+100% ADR: Open + ADR
+50% ADR: Open + 50% of ADR
−50% ADR: Open − 50% of ADR
−100% ADR: Open − ADR
Coverage %:
Tracks intraday high and low prices to calculate what percentage of the ADR has already been covered for the current session:
Coverage % = (High − Low) ÷ ADR × 100
Interactive Table:
Shows the ADR value and today's ADR coverage percentage in a customizable table overlay. The table position, colors, border, transparency, and an optional empty top row can all be adjusted via settings.
Customization Options
Table Settings:
Position the table (top/bottom × left/right).
Change background color, text color, border color and thickness.
Toggle an empty top row for spacing.
Line Settings:
Choose color, line style (solid/dotted/dashed), and width.
Lines automatically reposition each day based on that day's open price and ADR calculation.
General Inputs:
ADR length (number of days).
Smoothing method (RMA, SMA, EMA, WMA).
How to Use It for Trading
Measure Daily Movement: Instantly know the expected daily price range based on historical volatility.
Identify Overextension: Use the coverage % to see if the market has already moved close to or beyond its typical daily range.
Plan Entries & Exits: Align trade targets and stops with ADR levels for more objective intraday planning.
Visual Reference: Horizontal guide lines and table update automatically as new data comes in, helping traders stay informed without manual calculations.
Ideal For
Intraday traders tracking daily volatility limits.
Swing traders wanting a quick reference for expected price movement per day.
Anyone seeking a volatility-based framework for planning targets, stops, or identifying extended market conditions.
Indicator
Future is hereOverview
"Future is Here" is an original, multi-faceted Pine Script indicator designed to provide traders with a comprehensive toolset for identifying high-probability trading opportunities. By integrating volatility-based entry zones, trend-based price targets, momentum confirmation, dynamic support/resistance levels, and risk-reward ratio (RRR) calculations, this indicator offers a cohesive and actionable trading framework. Each feature is carefully designed to complement the others, ensuring a synergistic approach that enhances decision-making across various market conditions. This script is unique in its ability to combine these elements into a single, streamlined interface with clear visual cues and customizable alerts, making it suitable for both novice and experienced traders.
Key Features and How They Work Together
Volatility-Based Entry Zones
Purpose: Identifies overbought and oversold conditions using a volatility-adjusted moving average, helping traders spot potential reversal zones.
Mechanism: Utilizes a user-defined volatility length and multiplier to calculate dynamic overbought/oversold thresholds based on the standard deviation of price. Crossovers and crossunders of these levels trigger "Buy Zone" or "Sell Zone" labels.
Synergy: These zones act as the foundation for entry signals, which are later confirmed by momentum and trend filters to reduce false signals.
Trend-Based Price Targets
Purpose: Projects potential price targets based on the prevailing trend, giving traders clear objectives for profit-taking.
Mechanism: Combines a fast and slow moving average to determine trend direction, then calculates target prices using a multiplier of the price deviation from the slow MA. Labels display bullish or bearish targets when the fast MA crosses the slow MA.
Synergy: Works in tandem with entry zones and momentum signals to align targets with market conditions, ensuring traders aim for realistic price levels supported by trend strength.
Momentum Confirmation
Purpose: Validates entry signals by assessing momentum strength, filtering out weak setups.
Mechanism: Uses the momentum indicator to detect bullish or bearish momentum crossovers, labeling them as "Strong" or "Weak" based on a comparison with a smoothed momentum average.
Synergy: Enhances the reliability of buy/sell signals by ensuring momentum aligns with volatility zones and trend direction, reducing the risk of premature entries.
Dynamic Support/Resistance Levels
Purpose: Highlights key price levels where the market is likely to react, aiding in trade planning and risk management.
Mechanism: Detects pivot highs and lows over a user-defined lookback period, drawing horizontal lines for the most recent support and resistance levels (limited to two each for clarity). Labels mark these levels with price values.
Synergy: Complements entry zones and price targets by providing context for potential reversal or continuation points, helping traders set logical stop-losses or take-profits.
Buy/Sell Signals with Risk-Reward Ratios
Purpose: Generates precise buy/sell signals with integrated take-profit (TP), stop-loss (SL), and RRR calculations for disciplined trading.
Mechanism: Combines volatility zone crossovers, trend confirmation, and positive momentum to trigger signals. ATR-based TP and SL levels are calculated, and the RRR is displayed in labels for quick assessment.
Synergy: This feature ties together all previous components, ensuring signals are only generated when volatility, trend, and momentum align, while providing clear risk-reward metrics for trade evaluation.
Customizable Alerts
Purpose: Enables traders to stay informed of trading opportunities without constant chart monitoring.
Mechanism: Alert conditions are set for buy and sell signals, delivering notifications with the entry price for seamless integration into trading workflows.
Synergy: Enhances usability by allowing traders to act on high-probability setups identified by the indicator’s combined logic.
Originality
"Future is Here" is an original creation that distinguishes itself through its holistic approach to technical analysis. Unlike single-purpose indicators, it integrates volatility, trend, momentum, and support/resistance into a unified system, reducing the need for multiple scripts. The inclusion of RRR calculations directly in signal labels is a unique feature that empowers traders to evaluate trade quality instantly. The script’s design emphasizes clarity and efficiency, with cooldowns to prevent label clutter and a limit on support/resistance lines to maintain chart readability. This combination of features, along with its customizable parameters, makes it a versatile and novel tool for traders seeking a robust, all-in-one solution.
How to Use
Setup: Add the indicator to your PulseWire chart and adjust input parameters (e.g., Volatility Length, Trend Length, TP/SL Multipliers) to suit your trading style and timeframe.
Interpretation:
Look for "Buy Zone" or "Sell Zone" labels to identify potential entry points.
Confirm entries with "Bull Mom" or "Bear Mom" labels and trend direction (Bull/Bear Target labels).
Use Support/Resistance lines to set logical TP/SL levels or anticipate reversals.
Evaluate Buy/Sell signals with TP, SL, and RRR for high-probability trades.
Alerts: Set up alerts for Buy/Sell signals to receive real-time notifications.
Customization: Fine-tune multipliers and lengths to adapt the indicator to different markets (e.g., stocks, forex, crypto) or timeframes.
Indicator
ATR Buy, Target, Stop + OverlayATR Buy, Target, Stop + Overlay
This tool is to assist traders with precise trade planning using the Average True Range (ATR) as a volatility-based reference.
This script plots buy, target, and stop-loss levels on the chart based on a user-defined buy price and ATR-based multipliers, allowing for objective and adaptive trade management.
*NOTE* In order for the indicator to initiate plotted lines and table values a non-zero number must be entered into the settings.
What It Does:
Buy Price Input: Users enter a manual buy price (e.g., an executed or planned trade entry).
ATR-Based Target and Stop: The script calculates:
Target Price = Buy + (ATR × Target Multiplier)
Stop Price = Buy − (ATR × Stop Multiplier)
Customizable Timeframe: Optionally override the ATR timeframe (e.g., use daily ATR on a 1-hour chart).
Visual Overlay: Lines are drawn directly on the price chart for the Buy, Target, and Stop levels.
Interactive Table: A table is displayed with relevant levels and ATR info.
Customization Options:
Line Settings:
Adjust color, style (solid/dashed/dotted), and width for Buy, Target, and Stop lines.
Choose whether to extend lines rightward only or in both directions.
Table Settings:
Choose position (top/bottom, left/right).
Toggle individual rows for Buy, Target, Stop, ATR Timeframe, and ATR Value.
Customize text color and background transparency.
How to Use It for Trading:
Plan Your Trade: Enter your intended buy price when planning a trade.
Assess Risk/Reward: The script immediately visualizes the potential stop-loss and target level, helping assess R:R ratios.
Adapt to Volatility: Use ATR-based levels to scale stop and target dynamically depending on current market volatility.
Higher Timeframe ATR: Select a different timeframe for the ATR calculation to smooth noise on lower timeframe charts.
On-the-Chart Reference: Visually track trade zones directly on the price chart—ideal for live trading or strategy backtesting.
Ideal For:
Swing traders and intraday traders
Risk management and trade planning
Traders using ATR-based exits or scaling
Visualizing asymmetric risk/reward setups
How I Use This:
After entering a trade, adding an entry price will plot desired ATR target and stop level for visualization.
Adjusting ATR multiplier values assists in evaluating and planning trades.
Visualization assists in comparing ATR multiples to recent support and resistance levels.
Indicator
Session-Based Sentiment Oscillator [TradeDots]Track, analyze, and monitor market sentiment across global trading sessions with this advanced multi-session sentiment analysis tool. This script provides session-specific sentiment readings for Asian (Tokyo), European (London), and US (New York) markets, combining price action, volume analysis, and volatility factors into a comprehensive sentiment oscillator. It is an original indicator designed to help traders understand regional market psychology and capitalize on cross-session sentiment shifts directly on PulseWire.
📝 HOW IT WORKS
1. Multi-Component Sentiment Engine
Price Action Momentum : Calculates normalized price movement relative to recent trading ranges, providing directional sentiment readings.
Volume-Weighted Analysis : When volume data is available, incorporates volume flow direction to validate price-based sentiment signals.
Volatility-Adjusted Factors : Accounts for changing market volatility conditions by comparing current ATR against historical averages.
Weighted Combination : Merges all components using optimized weightings (Price: 1.0, Volume: 0.3, Volatility: 0.2) for balanced sentiment readings.
2. Session-Segregated Tracking
Automatic Session Detection : Precisely identifies active trading sessions based on user-configured time parameters.
Independent Calculations : Maintains separate sentiment accumulation for each major session, updated only during respective active hours.
Historical Preservation : Stores session-specific sentiment values even when sessions are closed, enabling cross-session comparison.
Real-Time Updates : Continuously processes sentiment during active sessions while preserving inactive session data.
3. Cross-Session Transition Analysis
Sentiment Differential Detection : Monitors sentiment changes when transitioning between trading sessions.
Configurable Thresholds : Generates signals only when sentiment shifts exceed user-defined minimum thresholds.
Directional Signals : Provides distinct bullish and bearish transition alerts with visual markers.
Smart Filtering : Applies smoothing algorithms to reduce false signals from minor sentiment variations.
⚙️ KEY FEATURES
1. Session-Specific Dashboard
Real-Time Status Display : Shows current session activity (ACTIVE/CLOSED) for all three major sessions.
Sentiment Percentages : Displays precise sentiment readings as percentages for easy interpretation.
Strength Classification : Automatically categorizes sentiment as HIGH (>50%), MEDIUM (20-50%), or LOW (<20%).
Customizable Positioning : Place dashboard in any corner with adjustable size options.
2. Advanced Signal Generation
Transition Alerts : Triangle markers indicate significant sentiment shifts between sessions.
Extreme Conditions : Diamond markers highlight overbought/oversold threshold breaches.
Configurable Sensitivity : Adjust signal thresholds from 0.05 to 0.50 based on trading style.
Alert Integration : Built-in PulseWire alert conditions for automated notifications.
3. Forex Currency Strength Analysis
Base/Quote Decomposition : For forex pairs, separates sentiment into individual currency strength components.
Major Currency Support : Analyzes USD, EUR, GBP, JPY, CHF, CAD, AUD, NZD strength relationships.
Relative Strength Display : Shows which currency is driving pair movement during active sessions.
4. Visual Enhancement System
Session Background Colors : Distinct background shading for each active trading session.
Overbought/Oversold Zones : Configurable extreme sentiment level visualization with colored zones.
Multi-Timeframe Compatibility : Works across all timeframes while maintaining session accuracy.
Customizable Color Schemes : Full color customization for dashboard, signals, and plot elements.
🚀 HOW TO USE IT
1. Add the Script
Search for "Session-Based Sentiment Oscillator " in the Indicators tab or manually add it to your chart. The indicator will appear in a separate pane below your main chart.
2. Configure Session Times
Asian Session : Set Tokyo market hours (default: 00:00-09:00) based on your chart timezone.
European Session : Configure London market hours (default: 07:00-16:00) for European analysis.
US Session : Define New York market hours (default: 13:00-22:00) for American markets.
Timezone Adjustment : Ensure session times match your broker's specifications and account for daylight saving changes.
3. Optimize Analysis Parameters
Sentiment Period : Choose 5-50 bars (default: 14) for sentiment calculation lookback period.
Smoothing Settings : Select 1-10 bars smoothing (default: 3) with SMA, EMA, or RMA options.
Component Selection : Enable/disable volume analysis, price action, and volatility factors based on available data.
Signal Sensitivity : Adjust threshold from 0.05-0.50 (default: 0.15) for transition signal generation.
4. Interpret Readings and Signals
Positive Values : Indicate bullish sentiment for the active session.
Negative Values : Suggest bearish sentiment conditions.
Dashboard Status : Monitor which session is currently active and their respective sentiment strengths.
Transition Signals : Watch for triangle markers indicating significant cross-session sentiment changes.
Extreme Alerts : Note diamond markers when sentiment reaches overbought (>70%) or oversold (<-70%) levels.
5. Set Up Alerts
Configure PulseWire alerts for:
- Bullish session transitions
- Bearish session transitions
- Overbought condition alerts
- Oversold condition alerts
❗️LIMITATIONS
1. Data Dependency
Volume Requirements : Volume-based analysis only functions when volume data is provided by your broker. Many forex brokers do not supply reliable volume data.
Price Action Focus : In absence of volume data, sentiment calculations rely primarily on price movement and volatility factors.
2. Session Time Sensitivity
Manual Adjustment Required : Session times must be manually updated for daylight saving time changes.
Broker Variations : Different brokers may have slightly different session definitions requiring time parameter adjustments.
3. Ranging Market Limitations
Trend Bias : Sentiment calculations may be less reliable during extended sideways or low-volatility market conditions.
Lag Consideration : As with all sentiment indicators, readings may lag during rapid market transitions.
4. Regional Market Focus
Major Session Coverage : Designed primarily for major global sessions; may not capture sentiment from smaller regional markets.
Weekend Gaps : Does not account for weekend gap effects on sentiment calculations.
⚠️ RISK DISCLAIMER
Trading and investing carry significant risk and can result in financial loss. The "Session-Based Sentiment Oscillator " is provided for informational and educational purposes only. It does not constitute financial advice.
- Always conduct your own research and analysis
- Use proper risk management and position sizing in all trades
- Past sentiment patterns do not guarantee future market behavior
- Combine this indicator with other technical and fundamental analysis tools
- Consider overall market context and your personal risk tolerance
This script is an original creation by TradeDots, published under the Mozilla Public License 2.0.
Session-based sentiment analysis should be used as part of a comprehensive trading strategy. No single indicator can predict market movements with certainty. Exercise proper risk management and maintain realistic expectations about indicator performance across varying market conditions. Indicator
Indicator
Market Flow Volatility Oscillator (AiBitcoinTrend)The Market Flow Volatility Oscillator (AiBitcoinTrend) is a cutting-edge technical analysis tool designed to evaluate and classify market volatility regimes. By leveraging Gaussian filtering and clustering techniques, this indicator provides traders with clear insights into periods of high and low volatility, helping them adapt their strategies to evolving market conditions. Built for precision and clarity, it combines advanced mathematical models with intuitive visual feedback to identify trends and volatility shifts effectively.
👽 How the Indicator Works
👾 Volatility Classification with Gaussian Filtering
The indicator detects volatility levels by applying Gaussian filters to the price series. Gaussian filters smooth out noise while preserving significant price movements. Traders can adjust the smoothing levels using sigma parameters, enabling greater flexibility:
Low Sigma: Emphasizes short-term volatility.
High Sigma: Captures broader trends with reduced sensitivity to small fluctuations.
👾 Clustering Algorithm for Regime Detection
The core of this indicator is its clustering model, which classifies market conditions into two distinct regimes:
Low Volatility Regime: Calm periods with reduced market activity.
High Volatility Regime: Intense periods with heightened price movements.
The clustering process works as follows:
A rolling window of data is analyzed to calculate the standard deviation of price returns.
Two cluster centers are initialized using the 25th and 75th percentiles of the data distribution.
Each price volatility value is assigned to the nearest cluster based on its distance to the centers.
The cluster centers are refined iteratively, providing an accurate and adaptive classification.
👾 Oscillator Generation with Slope R-Values
The indicator computes Gaussian filter slopes to generate oscillators that visualize trends:
Oscillator Low: Captures low-frequency market behavior.
Oscillator High: Tracks high-frequency, faster-changing trends.
The slope is measured using the R-value of the linear regression fit, scaled and adjusted for easier interpretation.
👽 Applications
👾 Trend Trading
When the oscillator rises above 0.5, it signals potential bullish momentum, while dips below 0.5 suggest bearish sentiment.
👾 Pullback Detection
When the oscillator peaks, especially in overbought or oversold zones, provide early warnings of potential reversals.
👽 Indicator Settings
👾 Oscillator Settings
Sigma Low/High: Controls the smoothness of the oscillators.
Smaller Values: React faster to price changes but introduce more noise.
Larger Values: Provide smoother signals with longer-term insights.
👾 Window Size and Refit Interval
Window Size: Defines the rolling period for cluster and volatility calculations.
Shorter windows: adapt faster to market changes.
Longer windows: produce stable, reliable classifications.
Disclaimer: This information is for entertainment purposes only and does not constitute financial advice. Please consult with a qualified financial advisor before making any investment decisions.
Indicator
Adaptive Volatility-Scaled Oscillator [AVSO] (Zeiierman)█ Overview
The Adaptive Volatility-Scaled Oscillator (AVSO) is a dynamic trading indicator that measures and visualizes volatility-adjusted market behavior. By scaling various metrics (such as volume, price changes, standard deviation, ATR, and Yang-Zhang volatility) and applying adaptive smoothing, AVSO helps traders identify market conditions where volatility deviates significantly from the norm.
This indicator uses standardized scaling (Z-Score logic) to highlight periods of abnormally high or low volatility relative to recent history. With gradient coloring and clear volatility zones, AVSO provides a visually intuitive way to analyze market volatility and adapt trading strategies accordingly.
█ How It Works
⚪ Scaling Metrics: The indicator scales user-selected metrics (e.g., volume, ATR, standard deviation) relative to the market and price, providing a standardized volatility measure.
⚪ Z-Score Standardization: The scaled metric is normalized using a Z-Score to measure how far current volatility deviates from its recent mean.
Positive Z-Score: Above-average volatility.
Negative Z-Score: Below-average volatility.
⚪ Adaptive Smoothing: An Adaptive EMA smooths the Z-Score, dynamically adjusting its length based on the strength of the volatility. Stronger deviations result in shorter smoothing, increasing responsiveness.
█ Unique Feature: Yang-Zhang Volatility
The Yang-Zhang volatility estimator sets this indicator apart by providing a more robust and accurate measure of volatility compared to traditional methods like ATR or standard deviation.
⚪ What Makes Yang-Zhang Volatility Unique?
Comprehensive Calculation: It combines overnight price gaps (log returns from the previous close to the current open) and intraday price movements (high, low, and close).
Accurate for Gapped Markets: Traditional volatility measures can misrepresent price movement when significant gaps occur between sessions. Yang-Zhang accounts for these gaps, making it highly reliable for assets prone to overnight price jumps, such as stocks, cryptocurrencies, and futures.
Adaptable to Real Market Conditions : By including both close-to-open returns and intraday volatility, it provides a balanced and adaptive measure that captures the full volatility picture.
⚪ Why This Matters to Traders
Better Volatility Insights: Yang-Zhang offers a clearer view of true market volatility, especially in markets with price gaps or uneven trading sessions.
Improved Trade Timing: By identifying volatility spikes and calm periods more effectively, traders can time their entries and exits with greater confidence.
█ How to Use
Identify High and Low Volatility
A high Z-Score (>2) indicates significant market volatility. This can signal momentum-driven moves, breakouts, or areas of increased risk.
A low Z-Score (<-2) suggests low volatility or a calm market environment. This often occurs before a potential breakout or reversal.
Trade Signals
High Volatility Zones (background highlight): Monitor for potential breakouts, trend continuations, or reversals.
Low Volatility Zones: Anticipate range-bound conditions or upcoming volatility spikes.
█ Settings
Source: Select the price source for scaling calculations (close, high, low, open).
Metric Measure: Choose the volatility measure:
Volume: Scales raw volume.
Close: Uses closing price changes.
Standard Deviation: Price dispersion.
ATR: Average True Range.
Yang: Yang-Zhang volatility estimate.
Bars to Analyze: Number of historical bars used to calculate the mean and standard deviation of the scaled metric.
ATR / Standard Deviation Period: Lookback period for ATR or Standard Deviation calculation.
Yang Volatility Period: Period for the Yang-Zhang volatility estimator.
Smoothing Period: Base smoothing length for the adaptive smoothing line.
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Disclaimer
The information contained in my Scripts/Indicators/Ideas/Algos/Systems does not constitute financial advice or a solicitation to buy or sell any securities of any type. I will not accept liability for any loss or damage, including without limitation any loss of profit, which may arise directly or indirectly from the use of or reliance on such information.
All investments involve risk, and the past performance of a security, industry, sector, market, financial product, trading strategy, backtest, or individual's trading does not guarantee future results or returns. Investors are fully responsible for any investment decisions they make. Such decisions should be based solely on an evaluation of their financial circumstances, investment objectives, risk tolerance, and liquidity needs.
My Scripts/Indicators/Ideas/Algos/Systems are only for educational purposes!
Indicator
Price Prediction With Rolling Volatility [TradeDots]The "Price Prediction With Rolling Volatility" is a trading indicator that estimates future price ranges based on the volatility of price movements within a user-defined rolling window.
HOW DOES IT WORK
This indicator utilizes 3 types of user-provided data to conduct its calculations: the length of the rolling window, the number of bars projecting into the future, and a maximum of three sets of standard deviations.
Firstly, the rolling window. The algorithm amasses close prices from the number of bars determined by the value in the rolling window, aggregating them into an array. It then calculates their standard deviations in order to forecast the prospective minimum and maximum price values.
Subsequently, a loop is initiated running into the number of bars into the future, as dictated by the second parameter, to calculate the maximum price change in both the positive and negative direction.
The third parameter introduces a series of standard deviation values into the forecasting model, enabling users to dictate the volatility or confidence level of the results. A larger standard deviation correlates with a wider predicted range, thereby enhancing the probability factor.
APPLICATION
The purpose of the indicator is to provide traders with an understanding of the potential future movement of the price, demarcating maximum and minimum expected outcomes. For instance, if an asset demonstrates a substantial spike beyond the forecasted range, there's a significantly high probability of that price being rejected and reversed.
However, this indicator should not be the sole basis for your trading decisions. The range merely reflects the volatility within the rolling window and may overlook significant historical price movements. As with any trading strategies, synergize this with other indicators for a more comprehensive and reliable analysis.
Note: In instances where the number of predicted bars is exceedingly high, the lines may become scattered, presumably due to inherent limitations on the PulseWire platform. Consequently, when applying three SD in your indicator, it is advised to limit the predicted bars to fewer than 80.
RISK DISCLAIMER
Trading entails substantial risk, and most day traders incur losses. All content, tools, scripts, articles, and education provided by TradeDots serve purely informational and educational purposes. Past performances are not definitive predictors of future results. Indicator
