RSI Divergence Hunter [JOAT]RSI Divergence Hunter
Automatically detects the four classic RSI divergence types on confirmed pivots and frames each one as a trade.
What it is
Divergence between price and momentum is one of the oldest reversal and continuation reads, but marking it by hand is subjective and easy to force. This indicator detects all four divergence types algorithmically on confirmed pivots, so what you see is defined and repeatable, and then attaches a full trade structure to each. It is an original divergence engine, not a plain RSI plot.
How it works
• RSI core — the relative strength index measures the speed and size of recent moves. It is the momentum reference every divergence is measured against.
• Confirmed pivots — the engine waits for pivots on both price and RSI to confirm a set number of bars back before comparing them. Because pivots are only evaluated once confirmed, a plotted divergence does not repaint into or out of existence.
• The four types — regular bullish (price lower low, RSI higher low) and regular bearish (price higher high, RSI lower high) point to potential reversals; hidden bullish and hidden bearish point to trend continuation after a pullback. Each is drawn with a connecting line on both price and RSI and labelled by type.
• Zones and gating — overbought and oversold zones give context, and a minimum-gap control keeps divergence signals from stacking on lower timeframes.
Trade levels
Each qualifying divergence draws a red risk box to the stop and a green reward box to the third target, with inner dividers and right-edge labels for entry, stop and each take-profit at your R multiples. The stop is anchored beyond the pivot that formed the divergence.
The dashboard
An adjustable divergence-scope panel shows the current RSI value and zone, the most recent divergence type detected, the active signal, a conviction estimate, and a live first-target-before-stop tally from closed bars only.
How to use it
• Works on any asset and timeframe.
• Treat regular divergences as counter-trend reversal cues and hidden divergences as with-trend continuation cues — the distinction matters.
• Combine with structure or a trend filter; divergence works well as confluence, not in isolation.
Settings
RSI length and source, pivot strength, which divergence types to display, overbought/oversold levels, risk multiple and target R multiples, plus visual and dashboard controls.
Originality and usefulness
The contribution is a complete, confirmed-pivot detector for all four divergence classes with clear per-type labelling and integrated, non-repainting trade framing. By fixing the definition of a divergence and waiting for pivot confirmation, it removes much of the hindsight bias that makes manual divergence unreliable.
Notes and limitations
• Divergence signals can persist and reappear in strong trends; a divergence is a condition, not a timing guarantee.
• Confirmed pivots introduce a natural delay equal to the pivot strength — this is the cost of not repainting.
• The tally reflects only past bars on the current chart and is not a forecast.
• Educational and analytical tool, not financial advice.
— made with passion by officialjackofalltrades
Indicator
Z-Score Flow Pro [JOAT]Z-SCORE FLOW PRO
A rigorously-statistical mean-reversion oscillator built on top of two of the cleanest primitives in market analysis — the Z-score of price against its own rolling mean and the EMA-smoothed RSI — and wrapped in a regime-aware visual and signal pipeline that knows when not to fire.
Why Z-score
A Z-score answers the question every reversion trader is really asking: "How many standard deviations is price from where it usually sits?" It is regime-aware by construction — when realised volatility expands, the same dollar move produces a smaller Z; when it contracts, the same dollar move produces a larger Z. That means the signal levels (Z = ±2, ±3, etc.) carry the same statistical meaning across instruments and timeframes, which a price-distance level never does.
Z-Score Flow Pro uses:
Z-score core — close vs SMA basis, normalised by rolling stdev, over a configurable lookback (default 100).
EMA trend filter — a long EMA (default 50) decides which side of the chart the engine considers in-regime. Signals are weighted by regime alignment, not blindly suppressed.
Smoothed RSI — RSI is computed, then EMA-smoothed (default 8-bar) to eliminate the single-bar whipsaws that plague the raw indicator without re-introducing visible lag.
A signal needs both the Z-score and the smoothed RSI to be at extremes on the same side — that AND-gating is what removes most of the false signals that pure RSI or pure Z systems produce.
Signal engine
A Buy signal requires Z ≤ Buy threshold (default −2.0) and smoothed RSI ≤ oversold level (default 30). A Sell signal requires Z ≥ Sell threshold (default +2.0) and smoothed RSI ≥ overbought level (default 70). A configurable cooldown prevents back-to-back signals; the labels respect the EMA regime filter so the strongest read is when signal direction agrees with the EMA trend.
Background heatmap (JOAT enhancement)
The chart pane is tinted bull or bear with an intensity proportional to |Z|. The mapping is linear: at Z = 0 the heatmap is nearly invisible, at |Z| = the saturation threshold (default 1.5) the tint reaches its loudest configured opacity. Both ends are tunable, so you can dial the heatmap from "barely there" to "institutional cockpit". This is the cleanest at-a-glance read of how stretched the market is right now — you do not need to read the Z value itself.
Divergence engine (JOAT enhancement)
A slope-comparison divergence runs in parallel: it compares the slope of the Z-score against the slope of price over a configurable lookback. A bullish divergence requires price slope negative and Z slope positive; bearish is the mirror. Both slopes must exceed a small epsilon to suppress flat-region noise, and a divergence cooldown spaces them out. Divergences print directly in the chart pane in the palette colour.
Slope-coloured Z-mean line
The Z-score's own running mean is plotted as a slope-coloured ribbon: bull / bear / flat colours based on the slope over a configurable sensitivity window. The shadow underneath the line uses an alpha-modulated version of the same colour so the line visually breathes with regime.
Dashboard
A compact monospaced table, positionable to any of nine corners, with togglable cell transparency. Rows surface:
Current Z-score and its direction (Rising / Falling / Flat).
One-year (252-bar) percentile of Z — how unusual the current reading is in its own recent history.
Smoothed RSI and its slope direction.
Active EMA regime (Up / Down / Neutral).
Distance of Z from its own min/max range (position-in-Z, 0–100%).
Alerts
Alerts are exposed for buy / sell signals, divergences, regime flips, and a configurable Z-extreme alert that fires when |Z| crosses a user-set high level (default 3.0). The extreme alert is the cleanest "the market is genuinely far from home" trigger this script produces and is suitable for end-of-day notification workflows.
How to read it
Three reads, in order of conviction:
Background heatmap — a glance tells you whether you are in a normal-Z regime (no tint) or stretched (bright tint). Most of the time, do nothing.
Signal labels — fade extremes only when both Z and RSI agree, and respect the EMA regime — counter-trend trades into a sustained EMA-aligned move are lower-conviction by definition.
Divergences — the highest-conviction reads. A bullish divergence with the heatmap saturated bear and the signal in the right direction is the cleanest setup the engine can produce.
Suggested settings
Defaults are tuned for 1H–4H on liquid markets. For 5m–15m, drop Z period to 50 and RSI period to 9. For daily and above, raise Z period to 200 and EMA trend filter to 100. The thresholds (±2.0 Z, 30/70 RSI) are intentionally classic — they correspond to the textbook two-sigma deviation and are well-understood; loosen them only if you are running on a less-liquid instrument.
Originality / what's reused
Z-score and RSI are public-domain mathematics, used here as primitives. The implementation — the smoothed-RSI gating, the slope-coloured Z-mean line with alpha shadow, the |Z|-driven background heatmap, the 252-bar percentile rank, the divergence epsilon filter, and the AND-gated signal pipeline — is JOAT-original and tuned together. No third-party code reused.
Open source
Published open-source under the default Mozilla Public License 2.0. Every section is banner-headed, every helper is documented inline, every input carries a tooltip. The Z-mean line, the heatmap, the divergence engine, and the dashboard are each in their own isolated module so you can study or adapt any single piece without reading the whole file.
Limitations
Z-score mean-reversion is a counter-trend tool by definition. In sustained one-sided trends the Z will live at an extreme for many bars and the signals will give back giveback — the EMA regime filter exists to warn you when you are in this state. The 252-bar percentile rank needs ~1 year of data to be meaningful; on shorter histories it warms up to neutral. Divergences are non-repainting but carry the natural lag of slope-over-window comparison.
—
-made with passion by jackofalltrades
Indicator
Tidal Divergence [JOAT]Tidal Divergence
Tidal Divergence is a composite divergence detector that lives in a sub-pane and projects high-conviction divergence visuals onto the price chart. The composite blends three volume-based oscillators — Money Flow Index, percentile-ranked Cumulative Volume Delta, and z-scored OBV rate-of-change — into a single normalized stream. Both regular and hidden divergences are detected. Persistent zones are drawn at divergence pivots, and zone mitigation is tracked with body / wick / rejection modes.
What makes it different
Single-oscillator divergence indicators give a single perspective. Tidal Divergence's composite triangulates three independent volume-derived oscillators so a divergence in the composite is supported by three volume readings instead of one.
Hidden divergences (continuation pattern: price higher low plus oscillator lower low for bull) are detected separately from regular divergences (reversal pattern), with distinct line styles on the price chart.
Each detected divergence creates a persistent demand or supply zone with optional FVG-confluence gating, dynamic alpha-by-age (zones fade as they age), and explicit mitigation logic (body / wick / two-close rejection variants).
A composite percentile envelope (5th to 95th percentile of the last 200 bars) is drawn behind the oscillator so absolute readings are easy to interpret in context.
How it works
MFI(14), daily-reset CVD then ta.percentrank(cvd, 100), OBV ROC z-score over a 20-bar mean / stdev. Three legs, each normalized to roughly the same scale.
Composite equals 0.40 times the normalized MFI plus 0.35 times the normalized CVD percentile plus 0.25 times the clamped OBV ROC z. Hull-smoothed and scaled to centi-percent.
Pivots are detected on the composite stream. A regular bull divergence requires a price lower low paired with a composite higher low within a 5-to-60-bar window. Hidden bull requires a price higher low plus composite lower low. Bear variants invert the conditions.
At each divergence pivot, two horizontal lines are drawn (edge equals lowest wick / highest wick. base equals lowest body / highest body), with a linefill between them, on the price chart via force_overlay=true.
Zone mitigation: body mode (close beyond edge) or wick mode (high/low beyond edge), optionally with two-close rejection requirement.
Optional FVG confluence requires a recent 3-bar Fair Value Gap before firing the divergence-final alert.
Reading the chart
In-pane : composite line tinted by direction with a smoothed signal line, gradient ribbon between them, breath-modulated zero midline, plus and minus 70 overbought / oversold thresholds, and the percentile envelope as an atmospheric backdrop.
In-pane divergence markers : regular divergences as solid connector plots, hidden divergences as broken (dashed-equivalent) connectors.
Cross-pane : price-to-price divergence connector lines on the price chart (regular solid, hidden dashed). Each line has a small REG BULL DIV 4520.50 or HID BEAR DIV label at the current pivot.
Cross-pane zone fills with age-graded transparency.
Zone edge price labels follow the right edge of each active zone.
Mitigation flash labels print at the bar where a zone is broken.
A cross-pane composite tint paints a soft mint / red background when the composite is clearly above or below plus or minus 30.
Signals
Regular bullish / bearish divergence
Hidden bullish / bearish divergence (continuation)
Bull / bear zone touch
Bull / bear zone mitigated
Bull / bear stack (three or more active zones plus a fresh regular divergence)
Bull / bear streak (composite above / below zero for N consecutive bars)
All gated on barstate.isconfirmed or barstate.ishistory. No future references. No lookahead_on.
Inputs
MFI : MFI length.
Divergence : pivot lookback left / right, detect hidden divergences toggle.
Zones : zone extreme length, max zone age, mitigation mode, allow-rejection toggle.
FVG Confluence : require FVG, FVG lookback bars.
Visual : bullish / bearish colors.
Cross-pane Visuals : divergence lines, divergence labels, zone edge labels, composite tint.
Dashboard : position, size.
How traders use this
Reversal entries : a regular bull divergence with the composite leaving an oversold extreme is a high-quality long setup, especially when accompanied by an FVG below the divergence price.
Continuation entries : a hidden bull divergence during a clearly trending bull regime is a structurally supported add-on entry on a pullback.
Zone trades : after a divergence prints, treat its zone as an active demand or supply level. Reactions to the zone (touch with rejection candles) are tradable. Mitigation invalidates the level.
Composite filter : only trade with the composite in agreement (composite above 0 for longs). The cross-pane tint helps you stay aligned without checking the pane.
Limitations
Divergence detection inherently lags the actual extreme by the right-pivot window.
Composite values are smoothed and need warm-up bars before they stabilize.
Cumulative Volume Delta is a tick-volume proxy, not true level-2 order flow.
A divergence is a probability, not a guarantee. Many divergences fail before completing their implied reversal.
Compatibility
Pine Script v6 open-source indicator (pane plus cross-pane). Any symbol with volume data. Cross-pane elements use force_overlay=true. No request.security calls.
Defaults
14-bar MFI, 14-left / 5-right pivot, body mitigation, FVG confluence off by default, mint / red palette, top-right medium dashboard. Enable FVG confluence to filter for higher-quality setups.
Indicator
Obsidian Divergence Ledger [JOAT]Obsidian Divergence Ledger
Introduction
Obsidian Divergence Ledger is an open-source divergence engine built around confirmed pivot logic and a composite oscillator. It tracks regular and hidden divergence, draws ledger lines between the relevant pivot points, and can optionally project those same relationships onto price. The design is meant to make divergence readable as a structured event instead of a vague visual impression.
The problem this script solves is that many divergence tools are either too loose or too noisy. They often compare incompatible pivots, ignore volatility context, or signal before the pivot is confirmed. Obsidian avoids that by waiting for confirmed pivot structures, enforcing minimum spread requirements, and optionally filtering signals through baseline context and volatility expansion.
Core Concepts
1. Composite Oscillator Construction
The script does not depend on one oscillator only. It blends RSI, CMO, and ROC into one composite measure, then normalizes and smooths it. This helps reduce the chance that one indicator-specific quirk dominates the entire divergence decision.
2. Pivot-Confirmed Divergence Logic
Divergence is only evaluated after `ta.pivothigh()` and `ta.pivotlow()` confirm the turning points. That means the signal appears later than an unconfirmed visual guess, but it also means the structure is stable and suitable for non-repainting use.
pricePivotHigh = ta.pivothigh(high, leftBars, rightBars)
pricePivotLow = ta.pivotlow(low, leftBars, rightBars)
3. Regular and Hidden Divergence
The script distinguishes between reversal-type divergence and continuation-type divergence:
Regular bullish: price makes a lower low while the oscillator makes a higher low
Regular bearish: price makes a higher high while the oscillator makes a lower high
Hidden bullish: price makes a higher low while the oscillator makes a lower low
Hidden bearish: price makes a lower high while the oscillator makes a higher high
4. Ledger Line Visualization and Divergence Zoning
Each confirmed event is recorded visually with lines on the oscillator pane. When enabled, price-side lines are also drawn on the main chart using `force_overlay = true`. Regular divergence and hidden divergence use different color families and line styles so reversal and continuation structures are easy to distinguish. Fresh divergence events can also paint oscillator-side pivot zones and price-side context boxes so the compared structure is visible as an area, not just a single line.
5. Context, Freshness, and Impulse Framing
The script tracks whether a divergence is still fresh, whether it aligns with baseline context, and whether current volatility supports the signal. A central impulse ribbon and intensity band expand and contract with current state strength so the pane itself carries more information even when the dashboard is kept compact.
Features
Composite oscillator: RSI, CMO, and ROC blended into one smoother divergence source
Confirmed pivots only: No divergence state is confirmed before pivot confirmation
Regular and hidden divergence: Reversal and continuation structures handled separately
Optional volatility filter: Can require expansion before accepting signals
Optional baseline filter: Can require directional context relative to a baseline
Oscillator and price ledger lines: Divergence is drawn in both the pane and the price chart when enabled
Oscillator pivot zones: Fresh divergence events can stamp colored zones around the compared oscillator pivots
Price context boxes: The related price swing area can be boxed directly on the chart for faster structural reading
On-chart divergence tags: Compact labels identify regular-vs-hidden bullish and bearish events on the chart itself
Impulse ribbon and intensity band: The pane carries fresh-state emphasis through layered fills, not only through text
Compact dashboard summary: State, freshness, oscillator bias, and context remain available in a smaller top-right panel
Input Parameters
Composite Oscillator:
RSI Length
CMO Length
ROC Length
Normalization Window
Oscillator Smoothing
Divergence Engine:
Pivot Left Bars and Pivot Right Bars
Hidden Divergence toggle
Maximum Ledger Lines
Quality Filters:
Volatility Expansion toggle and length
Baseline Context toggle and baseline length
Minimum Oscillator Pivot Spread
How to Use This Indicator
Step 1: Wait for a Confirmed State
Use the dashboard's State and Freshness rows first. The script is designed to treat confirmed divergence as the event, not the early suspicion of divergence.
Step 2: Separate Reversal From Continuation
Regular divergence is generally more useful when looking for exhaustion. Hidden divergence is generally more useful when looking for pullback continuation. The script keeps those two ideas separate on purpose.
Step 3: Read Context Before Weighting the Signal
A bullish divergence below a weak baseline can still fail. A bearish divergence into expanding volatility can still continue. Use the Context and Volatility rows before deciding how much weight to give the latest signal.
Step 4: Use the Zones, Not Only the Lines
The oscillator pivot zones and price context boxes are there to show the compared structure as an area. This is useful when a divergence is technically valid but forms in a narrow or low-importance pocket. A wider, cleaner zone often carries more practical significance than a tiny local pivot mismatch.
Step 5: Use the Price Overlay Lines as Reference
The overlay lines show the exact price pivots involved in the latest comparison. The companion price labels and boxes make it easier to judge whether the divergence formed in an important location or in minor local noise.
Indicator Limitations
Pivot confirmation creates intentional delay because the script waits for bars on the right side of each pivot
Divergence can persist through multiple additional swings before price meaningfully reverses
A composite oscillator reduces single-indicator bias but cannot eliminate false positives
Hidden divergence is context-dependent and is less useful if the broader trend is weak or unclear
Fresh divergence boxes and labels describe the compared structure, but they do not guarantee that the marked zone will react again
Originality Statement
Obsidian Divergence Ledger is original in the way it structures divergence as a confirmed ledger of relationships rather than a simple shape marker. The script combines a custom composite oscillator, explicit regular-vs-hidden separation, freshness tracking, context filters, synchronized pane-plus-price ledger lines, oscillator pivot zoning, and price-context divergence boxes into one coherent tool.
Disclaimer
This script is provided for educational and informational purposes only. It is not financial advice. Divergence is a contextual condition, not a guarantee of reversal or continuation. False signals can occur frequently, especially in strong trends and low-liquidity markets. Use independent confirmation and risk management.
Indicator
Equilibrium Momentum Shift + Divegence [BigBeluga]🔵 OVERVIEW
Equilibrium Momentum Shift is a range-based momentum oscillator designed to measure how far price has deviated from its current equilibrium.
Instead of focusing purely on trend direction or overbought/oversold conditions, this indicator evaluates price relative to the midpoint of its recent range and quantifies the strength of the shift away from that balance.
By combining normalized range deviation, smoothing techniques, and nonlinear compression, the indicator provides a clear view of when markets transition from equilibrium into directional momentum, now featuring Normal Divergence detection to spot potential trend reversals.
🔵 CONCEPT
Equilibrium Midpoint — The midpoint between the highest high and lowest low over the selected range length represents the equilibrium price.
Deviation Measurement — The indicator measures how far the current price has moved away from this midpoint.
Range Normalization — Deviations are normalized relative to the size of the current range, allowing the oscillator to remain consistent across different volatility conditions.
Momentum Compression — A hyperbolic tangent function compresses extreme values, stabilizing the oscillator and preventing runaway signals during large trends.
Divergence Identification — Automatically identifies discrepancies between price action and the oscillator to highlight weakening momentum in established trends.
🔵 HOW IT WORKS
1️⃣ Equilibrium Range Calculation
The indicator calculates the highest high and lowest low over the user-defined range length.
The midpoint between these two levels forms the equilibrium line.
This midline represents the center of balance for recent price activity.
2️⃣ Price Deviation Measurement
The distance between the current close and the equilibrium midpoint is calculated.
This deviation is then smoothed using a double EMA structure to reduce noise.
The smoothed value is normalized relative to half of the current range size.
3️⃣ Nonlinear Oscillator Transformation
A hyperbolic tangent function compresses normalized deviations into a stable range between -1 and +1.
This transformation prevents extreme outliers and creates a more interpretable oscillator.
4️⃣ Momentum Histogram
A signal line is generated using EMA smoothing.
The difference between the oscillator and the signal line forms a histogram.
The histogram behaves similarly to a MACD-style momentum indicator:
Expanding bars indicate strengthening momentum.
Contracting bars indicate weakening momentum.
5️⃣ Normal Divergence Logic
Bullish Divergence: Occurs when price makes a Lower Low , but the Equilibrium Oscillator makes a Higher Low . This suggests that despite the price drop, the selling pressure relative to equilibrium is fading.
Bearish Divergence: Occurs when price makes a Higher High , but the Equilibrium Oscillator makes a Lower High . This indicates that the buyers' ability to push price away from the midpoint is losing strength.
🔵 KEY FEATURES
Equilibrium midpoint plotted directly on the chart.
Range-normalized momentum oscillator.
Hyperbolic tangent compression to stabilize signals.
MACD-style histogram for momentum acceleration detection.
Automatic Normal Divergence labels to spot exhaustion.
Gradient-colored oscillator line reflecting directional bias.
Dashboard displaying real-time momentum metrics.
🔵 DASHBOARD METRICS
Shift — Current oscillator value showing how far price has moved from equilibrium.
State — Market regime derived from oscillator thresholds:
Bullish
Bearish
Neutral
Range Position — Location of price inside the current range expressed as a percentage.
Pressure — Magnitude of momentum deviation from equilibrium.
🔵 HOW TO USE
Use the equilibrium midline as a dynamic balance reference.
When the oscillator moves above zero, bullish momentum dominates.
When the oscillator moves below zero, bearish momentum dominates.
Trading Divergences: Watch for divergence labels when price is at historical range extremes. A bullish divergence near the "Lowest Low" of the range suggests a high-probability mean-reversion trade back toward equilibrium.
Histogram expansions highlight momentum acceleration.
Histogram contraction can signal potential momentum exhaustion.
🔵 INTERPRETING MOMENTUM SHIFTS
Oscillator near zero → Market is balanced around equilibrium.
Oscillator above 0.2 → Bullish momentum phase.
Oscillator below -0.2 → Bearish momentum phase.
Divergence Label + Oscillator Flatline → High probability of a trend reversal or deep pullback.
Rapid oscillator expansion → Strong directional pressure.
Oscillator flattening → Momentum compression or consolidation.
🔵 CONCLUSION
Equilibrium Momentum Shift offers a structured way to analyze how price behaves relative to its recent balance point.
By measuring normalized deviations from equilibrium and visualizing momentum shifts with a smoothed oscillator, histogram, and integrated divergence analysis , the indicator helps traders identify when markets transition from balance into directional movement.
This makes it especially useful for spotting early momentum expansions, trend continuation signals, and potential exhaustion points where price is likely to snap back to its equilibrium midpoint. Indicator
Tidal Volume Oscillator [JOAT]Tidal Volume Oscillator
Introduction
The Tidal Volume Oscillator is a separate-pane oscillator that attempts to answer a single question: is the current price movement being carried by genuine volume participation, or is it occurring on weak flow? It constructs a volume-weighted momentum score, normalizes it to a bounded range of −100 to +100, applies a Fourier-inspired exponential decay smoothing pass to reduce noise without introducing phase lag, and then scales the result with an adaptive trend filter. A flow momentum line tracks the acceleration of the oscillator itself. A divergence engine scans for all four divergence types simultaneously — regular bullish, regular bearish, hidden bullish, and hidden bearish — and plots them directly in the oscillator panel.
The indicator does not predict future price. It contextualizes current price movement relative to volume behavior and flags when price action and volume-weighted momentum are moving in opposite directions, which historically precedes changes in directional character — though not always, and not reliably in all instruments or conditions.
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Core Concepts
The VZO Foundation
The Volume Zone Oscillator (VZO) is an established concept that categorizes volume as positive or negative based on the direction of price change, then computes a ratio of positive to negative volume over a rolling window. This indicator rebuilds that concept from the ground up using a different normalization approach:
Relative Volume: Instead of using raw volume, the oscillator first normalizes each bar's volume against a rolling SMA of volume. This produces a relative volume reading — a value above 1.0 means the bar traded heavier than average, below 1.0 means lighter. This step removes the absolute scale of volume from the calculation, allowing the oscillator to behave comparably across instruments with vastly different volume profiles and across timeframes where absolute volume differs by orders of magnitude.
Volume-Weighted Momentum: The price change on each bar is smoothed via EMA, and the relative volume is separately smoothed via EMA. Multiplying these two smoothed values produces a volume-weighted momentum signal. This is then smoothed again to form a base momentum reading.
RSI-Style Normalization: Positive and negative portions of the base momentum are separated, each independently smoothed, and their ratio is fed into an RSI-style formula: vzo = 100 * (ratio - 1) / (ratio + 1) . This bounds the oscillator strictly between −100 and +100 and gives it a symmetric zero-line structure where positive values indicate dominant upward volume momentum and negative values indicate dominant downward volume momentum.
Fourier Exponential Decay Smoothing
After the initial VZO is computed, a second smoothing pass is applied using exponential decay weights. For each bar, the contribution of each of the prior N bars is weighted by exp(-i / (len * 0.3)) , where i is the number of bars back. This means the most recent bar carries maximum weight and each earlier bar contributes exponentially less. The window clips naturally as the weights approach zero.
The result is a smoothing pass that is inspired by frequency-domain thinking: it emphasizes recent values and de-emphasizes older values in a continuous decay rather than in the binary on/off fashion of a simple rolling average. The smoothed output tracks the oscillator's underlying shape while suppressing high-frequency noise without the phase shift that a centered moving average would introduce.
ADF Trend Filter
An adaptive multiplier is derived by comparing a short SMA and a long SMA of price, normalizing their difference by the rolling standard deviation of price over a matching window. This produces a dimensionless value that reflects the strength of the current trend relative to recent volatility — conceptually analogous to the logic behind an Augmented Dickey-Fuller trend test applied in a simplified real-time form.
This multiplier is kept close to 1.0 intentionally. Its role is not to dramatically change the oscillator's value but to apply a mild scaling that slightly amplifies the VZO when trend conditions are strong and slightly suppresses it during choppy, mean-reverting conditions. The effect is subtle but helps the oscillator's readings align better with the underlying market character.
Final Blended VZO
The final oscillator value blends the EMA-smoothed VZO and the Fourier-smoothed VZO according to a blend parameter, scales the result by the ADF multiplier, and clamps the output to the range. The blend parameter controls how much weight goes to the Fourier-smoothed version versus the EMA-smoothed version, allowing the user to tune between responsiveness and smoothness.
Flow Momentum Line
A secondary line is plotted alongside the main oscillator, computed as:
flow_momentum = (vzo - ema(vzo, lookback)) * 0.5
This measures the rate of change of the oscillator — its acceleration — and scales it to stay visually proportional. When the flow momentum line is rising, the oscillator is accelerating upward. When it is falling, the oscillator is losing momentum regardless of its absolute level. Crossovers between the oscillator and the flow momentum line can highlight inflection points in volume-weighted momentum.
Divergence Engine
The divergence engine uses pivot high and pivot low detection to identify four divergence types:
Regular Bullish Divergence: Price makes a lower low while the oscillator makes a higher low. Suggests weakening downward volume participation on the new price low.
Regular Bearish Divergence: Price makes a higher high while the oscillator makes a lower high. Suggests weakening upward volume participation on the new price high.
Hidden Bullish Divergence: Price makes a higher low while the oscillator makes a lower low. Often associated with pullbacks within an established uptrend where volume momentum remains stronger than the pullback's depth implies.
Hidden Bearish Divergence: Price makes a lower high while the oscillator makes a higher high. Often associated with rallies within an established downtrend where volume momentum is failing to confirm the price bounce.
The engine uses ta.valuewhen to retrieve the oscillator's value at the most recent prior pivot of the same type, then compares it to the current pivot. Lines and labels are drawn directly in the oscillator pane, keeping all divergence context in a single panel.
Dynamic Color Blending
The oscillator line and histogram (if enabled) use color blending that responds to both the direction of the oscillator and the intensity of the flow momentum. Colors transition smoothly between bull and bear palettes as conditions shift, with intensity modulated by momentum acceleration. This avoids binary color flips and gives a continuous visual read of the oscillator's strength and direction.
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Features
Relative-volume-normalized VZO foundation — removes absolute volume scale bias
RSI-style normalization producing a symmetric −100 to +100 oscillator
Fourier exponential decay smoothing pass for noise reduction without phase lag
ADF-inspired adaptive trend multiplier for regime-sensitive scaling
Blended output combining EMA and Fourier smoothing with user-adjustable weighting
Flow momentum line showing oscillator acceleration
Full four-type divergence engine: regular bull/bear and hidden bull/bear
Divergence lines and labels rendered directly in the oscillator pane
Dynamic color blending based on direction and momentum intensity
Overbought/oversold level lines at user-defined thresholds (default ±80)
Fully toggleable visual components including divergence types individually
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Input Parameters
VZO Length: Primary lookback for the volume-weighted momentum and normalization calculations (default: 14)
Smoothing Length: Short EMA length used in the initial volume-weighted momentum construction (default: 5)
Signal Length: EMA length applied to the final VZO for the signal/flow line (default: 9)
Fourier Window: Number of bars used in the exponential decay smoothing pass (default: 20)
Fourier Blend: Proportion of the final output taken from the Fourier-smoothed VZO versus the EMA-smoothed VZO (default: 0.4, meaning 40% Fourier / 60% EMA)
Overbought Level: Upper reference line threshold (default: +80)
Oversold Level: Lower reference line threshold (default: −80)
Pivot Bars: Number of bars on each side required to confirm a pivot high or low for divergence detection
Visual Toggles: Individual controls for divergence types (regular bull, regular bear, hidden bull, hidden bear), flow momentum line, bar coloring, and OB/OS lines
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How to Use
Reading the oscillator: Values above zero indicate that volume-weighted momentum favors buyers over the lookback window. Values below zero indicate it favors sellers. The magnitude reflects how dominant one side is. A reading of +60 is meaningfully different from +20 — the former suggests strong participation on the upside, the latter suggests modest positive lean.
Overbought/oversold levels: The default ±80 levels are deliberately set wide. Reaching ±80 indicates a statistically strong skew in volume momentum, not simply a directional bias. A reading at +85 that begins to decline is worth noting; a reading that has been above +80 for many bars without declining suggests strong persistent flow, not an automatic reversal condition.
Flow momentum line: Use the flow momentum line to identify when the oscillator is accelerating or decelerating. If the oscillator is above zero but the flow momentum line is falling and crossing below the oscillator, volume-weighted momentum is losing strength even if it has not crossed zero. This can be an early warning of a fading move.
Divergences: Divergence signals appear as labeled lines in the oscillator pane. They flag a disagreement between price structure and volume momentum structure. Regular divergences are typically associated with potential trend reversal conditions; hidden divergences are typically associated with trend continuation conditions during a pullback. Neither type is a standalone entry signal — they require context from price structure, higher timeframe trend, and other confirmation.
Combining types: A regular bearish divergence occurring while the oscillator is above +60 and the flow momentum line is declining is a more compelling condition than a divergence occurring at a neutral oscillator reading. Look for confluence between divergence signals, oscillator level, and flow momentum direction.
Timeframe notes: On lower timeframes, the divergence engine will fire frequently and many signals will resolve as noise. On higher timeframes, divergence signals are structurally more significant but rarer. The Fourier blend and VZO length should be calibrated to the timeframe being traded.
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Limitations
This indicator does not predict future price movement. All readings are computed from past and current bar data.
Volume data quality varies significantly across instruments and data providers. On instruments with unreliable, synthetic, or missing volume data (some forex pairs, certain CFDs, spread-betting instruments), the oscillator's readings will be distorted or meaningless.
Divergences are detected only at confirmed pivot points, which by definition require a lookback into past bars. A divergence signal will appear after the pivot is confirmed, not at the pivot bar itself. This is inherent to pivot-based divergence detection and is not a bug.
Hidden divergences can occur frequently during strong trends and produce many signals that resolve without follow-through on shorter timeframes.
The ADF-inspired filter is a simplified heuristic, not a formal statistical test. It does not guarantee that the adaptive scaling accurately reflects whether a market is trending or mean-reverting at any given moment.
The Fourier exponential decay smoothing is not a formal frequency-domain Fourier transform. The term is used descriptively to indicate the exponential weighting pattern, not to imply that the calculation resolves into sinusoidal components.
Extreme or sustained overbought/oversold readings do not guarantee a reversal. Strong trends can keep the oscillator pinned at extremes for extended periods.
The oscillator is bounded at ±100 by construction. This means that at extreme readings, additional strengthening of volume momentum does not move the line further — the clamping obscures incremental changes at extremes.
Past divergence performance on a given instrument is not indicative of future performance.
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Originality Statement
The VZO concept is established in the public domain. This implementation departs from the standard in several meaningful ways. Using relative volume (each bar's volume divided by a rolling SMA of volume) rather than raw volume removes the absolute scale of volume from the oscillator's behavior — a standard VZO applied to a futures contract and a low-float equity will behave differently purely due to volume magnitude; this version will not. The RSI-style normalization of the volume-weighted momentum ratio is retained from the VZO concept but is applied to a momentum signal constructed differently from the standard signed-volume approach. The Fourier exponential decay smoothing layer is an original addition: it is not a standard EMA, WMA, or VWMA — it applies a decaying weight function that is conceptually distinct from any standard Pine Script built-in smoothing function, producing a cleaner oscillator output with less phase distortion than an equivalent EMA. The ADF-inspired adaptive multiplier is a real-time regime-sensitivity mechanism not present in any standard oscillator. The four-type divergence engine built into the same panel, detecting all four divergence classes simultaneously using pivot comparison logic, provides complete divergence coverage without requiring additional scripts or manual line drawing. The combination of these elements — relative-volume normalization, Fourier decay smoothing, adaptive trend scaling, blended output, flow momentum line, and full-coverage divergence detection — into a single oscillator panel represents an original synthesis that is not replicated by any standard built-in indicator.
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Disclaimer
This indicator is provided for educational and informational purposes only. It does not constitute financial advice, investment advice, or a recommendation to buy or sell any financial instrument. Trading involves substantial risk of loss. Past performance of any indicator or strategy is not indicative of future results. Always conduct your own research and consult a qualified financial professional before making any trading decisions.
-Made with passion by officialjackofalltrades
Indicator
Chaos Regime Detection Engine [JOAT]Chaos Regime Detection Engine
Introduction
The Chaos Regime Detection Engine is an advanced open-source market microstructure indicator that classifies market conditions into distinct regimes using multi-dimensional volatility analysis, directional conviction measurement, and institutional flow detection. This indicator transforms raw market data into actionable regime intelligence, helping traders identify when markets are trending, ranging, chaotic, or experiencing volatility shocks.
Unlike single-dimension volatility indicators that only measure price movement magnitude, this engine analyzes market structure through four independent scoring systems that combine into a unified regime classification framework. The indicator is designed for traders who understand that different market regimes require different trading approaches and that regime identification is the foundation of adaptive strategy selection.
Why This Indicator Exists
This indicator addresses a fundamental challenge in trading: markets constantly shift between different behavioral regimes, and strategies that work in one regime often fail in another. The core innovation lies in synthesizing multiple market microstructure measurements into a probabilistic regime classification system:
Directional Flow Regime: Markets exhibiting high price efficiency, low choppiness, and strong ADX conviction - ideal for trend-following strategies
Equilibrium Regime: Markets showing balanced conditions with moderate volatility and weak directional bias - suitable for mean-reversion approaches
Chaotic Turbulence Regime: Markets displaying high choppiness, low efficiency, and conflicting signals - best avoided or traded with tight stops
Volatility Shock Regime: Markets experiencing extreme volatility expansion with high volume - requires defensive positioning or volatility strategies
Each regime classification is derived from normalized scores across multiple dimensions, ensuring that regime identification remains robust across different instruments, timeframes, and market conditions. The system provides not just regime labels but confidence levels and intensity measurements that quantify regime strength.
Core Components Explained
1. ATR and Volatility Percentile Analysis
The indicator calculates Average True Range (ATR) over a customizable period (default 14) and expresses it as a percentage of current price. This normalization allows cross-instrument comparison and removes price-level bias.
ATR percentile ranking over 100 bars provides context for current volatility relative to recent history. High percentile rankings (>70) indicate elevated volatility, while low rankings (<30) suggest compressed volatility. This percentile approach is superior to raw ATR because it adapts to each instrument's unique volatility characteristics.
The volatility percentile feeds into multiple regime scores, particularly the Volatility Shock score, which combines ATR percentile with standard deviation percentile and volume surge detection to identify extreme volatility events.
2. Kaufman Efficiency Ratio
The Efficiency Ratio measures how efficiently price moves from point A to point B by comparing net price change to total path length:
Efficiency = Net Price Change / Sum of Absolute Bar-to-Bar Changes
Values near 1.0 indicate highly efficient, directional movement (trending). Values near 0.0 indicate inefficient, choppy movement (ranging). The indicator uses a customizable lookback period (default 20) to calculate efficiency.
High efficiency feeds into the Directional Flow score, while low efficiency contributes to both Equilibrium and Chaotic Turbulence scores. This dual contribution ensures that the regime classification captures the full spectrum of market behavior.
3. Choppiness Index
The Choppiness Index quantifies market choppiness using logarithmic calculations:
Choppiness = 100 * log10(Sum of ATR / (Highest High - Lowest Low)) / log10(Length)
Values above 61.8 indicate choppy, range-bound markets. Values below 38.2 indicate trending markets. The indicator uses a customizable period (default 14) for this calculation.
The Choppiness Index is inverted when contributing to the Directional Flow score (100 - Choppiness) because low choppiness indicates high directional clarity. High choppiness directly contributes to the Chaotic Turbulence score, identifying markets where price action lacks clear direction.
4. ADX Directional Conviction System
The indicator implements a complete ADX (Average Directional Index) calculation including +DI and -DI components:
+DI measures upward directional movement strength
-DI measures downward directional movement strength
ADX measures the strength of directional movement regardless of direction
ADX values above the trend threshold (default 25) indicate emerging directional conviction. Values above the strong threshold (default 40) indicate dominant directional conviction. The indicator uses customizable lengths for both DI calculation (default 14) and ADX smoothing (default 14).
ADX contributes bonus points to the Directional Flow score when above threshold and to the Equilibrium score when below threshold. The difference between +DI and -DI provides directional bias (long vs short) and conviction strength measurements.
5. Standard Deviation and RVI Analysis
Standard deviation of close prices over 20 bars provides an alternative volatility measurement that captures price dispersion rather than range. The indicator calculates standard deviation as a percentage of price and ranks it using percentile analysis.
The Relative Volatility Index (RVI) applies standard deviation concepts to directional movement:
RVI = 100 * StdDev(Up Moves) / (StdDev(Up Moves) + StdDev(Down Moves))
RVI values above 50 indicate upward volatility dominance, below 50 indicates downward volatility dominance. This provides directional context to volatility measurements that raw standard deviation lacks.
Both metrics contribute to the Volatility Shock score, helping identify when markets are experiencing not just high volatility but directionally biased volatility expansion.
6. Volume Delta Integration
The indicator estimates buying and selling pressure using volume and candle structure:
Buy Volume = Volume when close > open
Sell Volume = Volume when close < open
Volume surge detection compares current volume to 20-period average using a customizable threshold (default 1.5x). Volume surges add bonus points to the Volatility Shock score, confirming that volatility expansion is accompanied by genuine institutional participation rather than thin-market noise.
This volume integration ensures that regime classifications reflect actual market activity rather than just price movement patterns.
7. Regime Scoring and Classification Engine
The indicator calculates four independent regime scores (0-100 scale):
Directional Score = (Efficiency * 100 + (100 - Choppiness) + ADX Bonus) / 2.2
Equilibrium Score = (100 - ATR Percentile + (100 - Efficiency * 100) + ADX Penalty) / 2.2
Turbulence Score = (Choppiness + (100 - Efficiency * 100)) / 2
Shock Score = (ATR Percentile + StdDev Percentile + Volume Surge Bonus) / 2.3
These scores are then normalized to sum to 100%, creating a probability distribution across the four regimes. The dominant regime is determined by the highest normalized score, with confidence level equal to that score's magnitude.
Regime intensity is classified as Nascent (score 35-45), Established (score 45-60), or Dominant (score >60), providing additional context about regime strength and stability.
8. Fractal Divergence Detection
The indicator implements fractal-based divergence detection using a composite volatility index that combines:
30% ATR Percentile
20% Efficiency Ratio
20% Inverted Choppiness
15% StdDev Percentile
15% RVI
This composite index is smoothed with a 5-period EMA and analyzed for fractal tops and bottoms using a 5-bar pattern recognition system. Divergences are detected when price makes new highs/lows but the composite volatility index fails to confirm, suggesting hidden institutional positioning or liquidity asymmetries.
Regular divergences signal potential reversals, while hidden divergences suggest trend continuation after pullbacks. The indicator plots these divergences with color-coded markers and draws connecting lines for visual clarity.
Visual Elements
Composite Volatility Line: Main plot showing the smoothed composite volatility index with dynamic gradient coloring based on regime confidence
Regime Intensity Histogram: Histogram showing regime-specific intensity with transparency based on confidence level
Microstructure Indicators: Subtle circle plots showing ATR percentile, efficiency ratio, and directional clarity for detailed analysis
Conviction Overlay: Stepline plot showing ADX with gradient coloring based on conviction strength
Fractal Divergence Markers: Circle plots at fractal tops/bottoms with color-coded divergence identification
Regime Threshold Lines: Horizontal lines at key regime transition levels (50, 60, 40, 75, 25)
Probability Zone Fill: Subtle background fill showing current regime probability field
Signal Shapes: Triangle shapes on price chart for high-confidence regime transitions and divergences
Comprehensive Dashboard: 12-row intelligence panel showing regime state, certainty, bias, probability scores, conviction, confluence, and all key metrics
The dashboard provides at-a-glance regime assessment with color-coded values, status indicators, and confidence measurements for all regime dimensions simultaneously.
Input Parameters
Signal Architecture:
Regime Shift Signals: Toggle chaos-to-order transition detection (default enabled)
Regime Persistence Signals: Toggle regime stability confirmations (default enabled)
Fractal Divergence Detection: Toggle hidden liquidity flow asymmetries (default enabled)
Minimum Confluence Threshold: Multi-factor validation requirement (1-5, default 3)
Volatility Microstructure:
Volatility Expansion Period: ATR calculation length (5-50, default 14)
Volatility Percentile Window: Percentile ranking lookback (20-500, default 100)
Price Efficiency Horizon: Efficiency ratio calculation period (5-100, default 20)
Chaos Measurement Period: Choppiness index length (5-50, default 14)
Directional Conviction:
Conviction Measurement Length: DI calculation period (5-50, default 14)
Conviction Smoothing Factor: ADX smoothing length (1-50, default 14)
Conviction Emergence Level: ADX trend threshold (15-40, default 25)
Conviction Dominance Level: ADX strong threshold (30-60, default 40)
Institutional Flow:
Enable Flow Asymmetry Detection: Toggle volume delta analysis (default enabled)
Flow Surge Multiplier: Volume threshold for surge detection (1.0-5.0, default 1.5)
Regime Parameters:
Directional Regime Threshold: Score required for directional classification (50-90, default 60)
Chaotic Regime Threshold: Score required for chaos classification (10-50, default 40)
Volatility Shock Threshold: Score required for shock classification (25-50, default 35)
Visualization:
Regime Intelligence Panel: Toggle dashboard display (default enabled)
Microstructure Indicators: Toggle detailed metric plots (default enabled)
Regime Probability Zones: Toggle background probability field (default enabled)
Intelligence Panel Scale: Small/Normal/Large dashboard sizing (default Normal)
Colors:
All colors are fully customizable including directional expansion (neon cyan), volatility shock (neon pink), equilibrium state (gold), and chaotic turbulence (sunset orange).
How to Use This Indicator
Step 1: Identify Current Regime
Check the dashboard "STATE" field to see current regime classification. Note the intensity level (Nascent/Established/Dominant) and certainty percentage. Dominant regimes with high certainty (>80%) are most reliable for strategy selection.
Step 2: Assess Regime Certainty
Monitor the "CERTAINTY" metric. High certainty (>60%) indicates clear regime conditions where strategies aligned with that regime should perform well. Low certainty (<40%) suggests transitional conditions where defensive positioning is appropriate.
Step 3: Check Directional Bias
Review the "BIAS" field showing Long Flow, Short Flow, or Neutral. This indicates whether directional conviction favors long or short positioning within the current regime. The numerical value shows conviction strength.
Step 4: Analyze Regime Probability Scores
Examine the four regime probability scores (Directional, Equilibrium, Turbulence, Shock). These show the relative likelihood of each regime. When one score dominates (>60%), regime classification is clear. When scores are balanced, market is transitional.
Step 5: Monitor Conviction Metrics
Check "CONVICTION" showing ADX value and status (Dominant/Emerging/Absent). Dominant conviction (>40) confirms that directional regimes have strong follow-through potential. Absent conviction (<25) suggests equilibrium or chaotic conditions.
Step 6: Evaluate Confluence Matrix
Review the "CONFLUENCE" score (0-5) showing how many confirmation factors align. Maximum confluence (5/5) indicates all factors agree, providing highest-confidence regime classification. Low confluence (1-2/5) suggests conflicting signals requiring caution.
Step 7: Watch for Regime Transitions
Regime transition signals (triangles on price chart) mark shifts between regimes. These are critical moments for strategy adjustment. Transitions from Chaos to Directional often mark the start of new trends. Transitions to Shock regimes warn of elevated risk.
Step 8: Use Divergence Signals
Fractal divergence markers (labeled "DIV") identify price-volatility asymmetries that often precede regime changes. Bullish divergences in Equilibrium regimes may signal upcoming Directional regimes. Bearish divergences in Directional regimes may warn of regime exhaustion.
Best Practices
Use Directional Flow regimes for trend-following strategies with trailing stops
Use Equilibrium regimes for mean-reversion strategies with defined profit targets
Avoid new positions during Chaotic Turbulence regimes or use very tight stops
Reduce position size or hedge during Volatility Shock regimes
Regime transitions with high confluence (4-5/5) offer highest-probability strategy shift opportunities
Dominant intensity regimes (>60% certainty) are most reliable for strategy execution
Nascent intensity regimes (<45% certainty) require defensive positioning until regime establishes
Monitor conviction metrics - Directional regimes without conviction (ADX <25) often fail
Fractal divergences are most reliable when they occur at regime extremes
Use the probability scores to anticipate regime transitions before they're officially classified
Equilibrium regimes with rising Directional scores suggest impending breakouts
Directional regimes with rising Turbulence scores warn of trend exhaustion
Indicator Limitations
Regime classification is probabilistic, not deterministic - no regime guarantees specific outcomes
The indicator identifies current regime but cannot predict regime duration
Regime transitions can be whipsaw-prone during genuinely transitional market conditions
Volume-based components require accurate volume data - some instruments have unreliable volume
The indicator works best on liquid instruments with consistent trading patterns
Newly listed instruments may lack sufficient history for reliable percentile calculations
Extreme market events (flash crashes, circuit breakers) can temporarily distort regime classification
The indicator shows what regime exists, not why - fundamental catalysts can override regime signals
Confluence scoring requires all factors to be relevant - some factors may be less meaningful on certain instruments
Fractal divergence detection requires clear fractal formation - choppy markets may produce false divergences
Regime intensity classifications are relative to recent history, not absolute across all market conditions
Technical Implementation
Built with Pine Script v6 using:
Complete ADX calculation with +DI/-DI components and customizable smoothing
Kaufman Efficiency Ratio using net change vs path length methodology
Choppiness Index with logarithmic normalization
Multi-component composite volatility index with weighted factor contributions
Percentile ranking calculations for ATR, standard deviation, and composite volatility
Fractal pattern recognition using 5-bar pivot detection
Divergence detection comparing price fractals to volatility fractals
Four-dimensional regime scoring system with normalization to probability distribution
Confluence factor calculation combining conviction, flow, clarity, certainty, and efficiency
Dynamic color gradients based on regime confidence and intensity
Comprehensive dashboard with 12 metrics and color-coded status indicators
Alert system for regime transitions, divergences, and conviction surges
The code is fully open-source with extensive comments explaining each calculation and regime classification logic.
Originality Statement
This indicator is original in its multi-dimensional regime classification approach. While individual components (ATR, Efficiency Ratio, Choppiness, ADX) are established concepts, this indicator is justified because:
It synthesizes four independent regime scoring systems into a unified probabilistic classification framework
The composite volatility index combines five distinct measurements with optimized weighting
Regime intensity classification (Nascent/Established/Dominant) provides confidence context beyond simple regime labels
Confluence scoring validates regime classification through multi-factor confirmation
Fractal divergence detection identifies hidden institutional positioning through volatility-price asymmetries
The normalization of regime scores to probability distribution ensures consistent interpretation across instruments
Integration of volume surge detection confirms that regime classifications reflect genuine market activity
The dashboard synthesizes 12 distinct metrics into a unified regime intelligence panel
Regime transition signals with confluence filtering provide high-confidence strategy adjustment points
The system adapts to each instrument's unique characteristics through percentile-based calculations
Each component contributes unique intelligence: ATR measures volatility magnitude, Efficiency measures directional clarity, Choppiness measures range-bound behavior, ADX measures conviction, volume confirms participation, and divergences reveal hidden positioning. The indicator's value lies in combining these complementary perspectives into a cohesive regime classification system that guides strategy selection.
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. Trading involves substantial risk of loss and is not suitable for all investors.
Regime classification is probabilistic analysis that identifies current market conditions but does not predict future regime duration or transitions. Regime signals do not guarantee profitable trades. Past regime patterns do not guarantee future regime patterns. Market conditions change, and strategies that worked in historical regimes may not work in future regimes.
The metrics displayed are mathematical calculations based on current market data, not predictions of future price movement. Regime transitions, divergences, and confluence scores do not guarantee profitable trades. Users must conduct their own analysis and risk assessment before making trading decisions.
Always use proper risk management, including stop losses and position sizing appropriate for your account size and risk tolerance. Never risk more than you can afford to lose. Consider consulting with a qualified financial advisor before making investment decisions.
The author is not responsible for any losses incurred from using this indicator. Users assume full responsibility for all trading decisions made using this tool.
-Made with passion by officialjackofalltrades Indicator
Momentum Pressure Gauge [JOAT] Momentum Pressure Gauge
Introduction
The Momentum Pressure Gauge is an advanced institutional-grade analysis tool designed to measure the underlying buying and selling pressure that drives market movements. This indicator goes beyond simple momentum oscillators by quantifying the actual pressure differential between buyers and sellers, incorporating volume analysis, detecting divergences, and identifying when momentum is reaching extreme levels. Understanding pressure and momentum is crucial because price often follows pressure - by measuring the force behind price movements, traders can anticipate future direction with greater confidence.
This tool is built for traders who understand that markets are driven by the constant battle between buyers and sellers, and that the outcome of this battle is reflected in pressure and momentum patterns. Whether you're a day trader timing entries with precision, a swing trader identifying trend strength, or a position trader spotting major reversals, this gauge provides the sophisticated pressure analysis needed to trade with the dominant force rather than against it.
Why This Indicator Exists
Most traders use basic momentum indicators without understanding the underlying pressure dynamics or volume participation. This indicator addresses that limitation by:
Pressure Analysis: Measures actual buying/selling pressure in each bar
Volume Weighting: Incorporates volume to confirm pressure significance
Momentum Scoring: Provides composite momentum scores with multiple factors
Divergence Detection: Identifies price/momentum divergences for early reversal signals
Extreme Zone Identification: Flags overbought/oversold conditions with pressure context
Energy Wave Analysis: Combines pressure with volume and price energy
The gauge transforms abstract momentum concepts into concrete pressure measurements that reveal the true force behind market movements.
Core Components Explained
1. Raw Pressure Calculation
The indicator measures buying and selling pressure in each bar:
// Raw buying/selling pressure
f_pressure_raw() =>
float range_val = high - low
float buy_pressure = range_val > 0 ? (close - low) / range_val : 0.5
float sell_pressure = range_val > 0 ? (high - close) / range_val : 0.5
// Apply smoothing
float pressure_ratio = ta.ema(raw_buy, i_pressure_len)
float pressure_smooth = ta.ema(pressure_ratio, i_smooth_len)
Pressure components:
Buy Pressure: Where price closed within the bar's range (0-1)
Sell Pressure: Complementary sell pressure (0-1)
Pressure Ratio: Buy pressure as a ratio
Smoothing: EMA smoothing for cleaner signals
Range Normalization: Pressure relative to bar's range
Pressure above 0.5 indicates buying dominance, below 0.5 indicates selling dominance.
2. Volume-Weighted Pressure
Volume analysis confirms the significance of pressure:
// Volume relative strength
float vol_sma = ta.sma(volume, i_pressure_len)
float vol_ratio = vol_sma > 0 ? volume / vol_sma : 1.0
float vol_weight = math.min(vol_ratio, 3.0) / 3.0 // Cap at 3x average
// Volume-weighted pressure
float vw_pressure = pressure_smooth * (0.7 + vol_weight * 0.3)
// Cumulative pressure
float cum_pressure = ta.sma(raw_buy, i_pressure_len) - 0.5 // Centered at 0
Volume features:
Volume Ratio: Current volume relative to average
Volume Weight: Normalized volume influence (0-1)
VW Pressure: Pressure adjusted for volume participation
Cumulative Pressure: Running pressure average
Volume Cap: Prevents extreme volume from distorting signals
High volume confirms pressure significance, while low volume questions its reliability.
3. Momentum Analysis
Multiple momentum factors are combined for comprehensive analysis:
// Pressure momentum (rate of change)
float pressure_momentum = pressure_smooth - pressure_smooth
// Pressure acceleration
float pressure_accel = pressure_momentum - pressure_momentum
// Composite pressure score (-100 to +100)
float composite_score = (pressure_smooth - 0.5) * 200
// Momentum-adjusted score
float momentum_adjustment = pressure_momentum * 100
float adjusted_score = composite_score + momentum_adjustment * 0.3
Momentum components:
Pressure Momentum: Rate of change in pressure
Pressure Acceleration: Change in momentum (second derivative)
Composite Score: Normalized pressure score (-100 to +100)
Momentum Adjustment: Score adjusted for momentum
Acceleration Detection: Identifies momentum shifts
Momentum analysis reveals not just current pressure but its direction and acceleration.
4. WaveTrend Integration
The WaveTrend oscillator adds an additional momentum layer:
f_wavetrend(int channel_len, int avg_len) =>
float ap = hlc3
float esa = ta.ema(ap, channel_len)
float d = ta.ema(math.abs(ap - esa), channel_len)
float ci = d > 0 ? (ap - esa) / (0.015 * d) : 0.0
float wt1_local = ta.ema(ci, avg_len)
float wt2_local = ta.sma(wt1_local, 4)
// WaveTrend signals
bool wt_bullish = wt1 > wt2 and wt1 > wt1
bool wt_bearish = wt1 < wt2 and wt1 < wt1
bool wt_oversold = wt1 < -60
bool wt_overbought = wt1 > 60
WaveTrend features:
WT1/WT2 Lines: Fast and slow WaveTrend lines
Cross Signals: Line crossovers for momentum changes
Extreme Levels: Overbought (>60) and oversold (<-60)
Trend Confirmation: Line slope for additional confirmation
Integration: Combined with pressure for confluence
WaveTrend provides an independent momentum confirmation.
5. Energy Wave Calculation
The indicator combines multiple energy sources:
// Energy combines pressure momentum with volume energy
float vol_energy = vol_sma > 0 ? (volume - vol_sma) / vol_sma * 100 : 0
float atr_14 = ta.atr(14)
float price_energy = atr_14 > 0 ? (close - open) / atr_14 * 100 : 0
float combined_energy = (pressure_momentum * 100 + vol_energy * 0.3 +
price_energy * 0.2) / 1.5
float energy_smooth = ta.ema(combined_energy, 5)
Energy components:
Volume Energy: Volume deviation from average
Price Energy: Price movement relative to ATR
Pressure Energy: Momentum contribution
Combined Energy: Weighted average of all energies
Energy Smoothing: EMA for cleaner energy signals
Energy waves show the underlying power driving market movements.
6. Divergence Detection
The indicator identifies price/momentum divergences:
// Price direction
float price_change = close - close
int price_dir = price_change > 0 ? 1 : price_change < 0 ? -1 : 0
// Pressure direction
int pressure_dir = pressure_momentum > i_momentum_thresh ? 1 :
pressure_momentum < -i_momentum_thresh ? -1 : 0
// Divergence detection
bool bullish_divergence = price_dir == -1 and pressure_dir == 1
bool bearish_divergence = price_dir == 1 and pressure_dir == -1
Divergence types:
Bullish Divergence: Price falling but pressure rising
Bearish Divergence: Price rising but pressure falling
Hidden Divergence: Continuation patterns
Regular Divergence: Reversal patterns
Threshold Filter: Minimum momentum for valid divergence
Divergences often precede significant price reversals.
7. State Classification System
The indicator classifies market states based on pressure:
// Pressure state
// 2 = extreme buying, 1 = buying, 0 = neutral, -1 = selling, -2 = extreme selling
var int pressure_state = 0
if pressure_smooth >= i_extreme_high
pressure_state := 2
else if pressure_smooth > 0.5 + i_momentum_thresh
pressure_state := 1
else if pressure_smooth <= i_extreme_low
pressure_state := -2
else if pressure_smooth < 0.5 - i_momentum_thresh
pressure_state := -1
// Momentum state
// 1 = accelerating, 0 = steady, -1 = decelerating
var int momentum_state = 0
if pressure_accel > i_momentum_thresh / 2
momentum_state := 1
else if pressure_accel < -i_momentum_thresh / 2
momentum_state := -1
State meanings:
Extreme Buying: Maximum buying pressure (>70%)
Buying: Moderate buying pressure (50-70%)
Neutral: Balanced pressure (40-60%)
Selling: Moderate selling pressure (30-50%)
Extreme Selling: Maximum selling pressure (<30%)
Accelerating: Momentum increasing
Decelerating: Momentum decreasing
State classification provides clear, actionable market conditions.
Visual Elements
Pressure Histogram: Main pressure display with gradient coloring
Multi-Layer Glow: Intensity-based glow effects
Energy Wave: Separate energy visualization
Momentum Line: Momentum rate of change
WaveTrend Lines: Additional momentum confirmation
Divergence Markers: Visual divergence signals
Extreme Zones: Highlighted overbought/oversold areas
Dashboard: Comprehensive metrics panel
Signal Labels: Key event labels with spacing
The dashboard displays:
1. Current pressure state and intensity
2. Momentum state and acceleration
3. Composite score and direction
4. Volume weight and analysis
5. Divergence status and alerts
6. Energy wave readings
7. Confluence quality score
8. WaveTrend status and signals
9. Overall signal strength
Input Parameters
Pressure Settings:
Pressure Period: Pressure calculation period (default: 14)
Smoothing Period: EMA smoothing (default: 5)
Momentum Lookback: Momentum calculation (default: 10)
Thresholds:
Extreme Buying: Maximum buying level (default: 0.7)
Extreme Selling: Maximum selling level (default: 0.3)
Momentum Threshold: Minimum momentum (default: 0.05)
WaveTrend Settings:
Channel Length: WT calculation period (default: 9)
Average Length: WT smoothing period (default: 12)
Enable WT: Toggle WaveTrend on/off
Visual Settings:
Color Scheme: Customizable pressure colors
Glow Effects: Enable visual enhancements
Show Zones: Display extreme zones
Show Labels: Control signal label frequency
How to Use This Indicator
Step 1: Assess Pressure State
Check the dashboard for current pressure state. Extreme states (>70% or <30%) often precede reversals, while moderate states suggest continuation.
Step 2: Analyze Momentum
Look at momentum direction and acceleration. Accelerating momentum in the pressure direction confirms strength, while deceleration warns of potential reversals.
Step 3: Check Volume Confirmation
Ensure pressure is supported by volume. High volume pressure is more reliable than low volume pressure.
Step 4: Watch for Divergences
Divergences are powerful reversal signals. A bullish divergence (price down, pressure up) suggests buying opportunity, while bearish divergence suggests selling.
Step 5: Monitor Energy Waves
Energy waves show the underlying power. Rising energy confirms current pressure, while falling energy suggests weakening.
Step 6: Use Extreme Zones
Extreme buying (>70%) often marks tops, while extreme selling (<30%) often marks bottoms. These are contrarian signals.
Best Practices
Extreme pressure states (>70% or <30%) often precede reversals
Divergences are most reliable at extreme levels
Volume confirmation is essential - pressure without volume is suspect
Momentum acceleration confirms pressure strength
Energy waves provide early warning of momentum shifts
Multiple timeframe analysis improves signal reliability
Combine with trend analysis for optimal results
Use WaveTrend crossovers for additional confirmation
Keep a pressure journal to track patterns
Be patient for the highest quality setups
Trading Applications
Momentum Trading:
Enter when pressure > 60% and accelerating
Add to positions as momentum increases
Exit when pressure decelerates or reverses
Use volume to confirm signal strength
Reversal Trading:
Look for extreme pressure (>70% or <30%)
Wait for divergence confirmation
Enter on first sign of pressure reversal
Target mean reversion to 50% level
Divergence Trading:
Identify clear price/pressure divergences
Confirm with volume and energy analysis
Enter on momentum shift confirmation
Use tight stops due to reversal nature
Strategy Integration
This indicator enhances any trading system:
Use pressure as a trend confirmation filter
Import momentum scores for signal weighting
Apply divergence detection for early warnings
Use extreme zones for contrarian signals
Integrate volume-weighted pressure for confirmation
Export pressure states for custom logic
Technical Implementation
Built with Pine Script v6 featuring:
Advanced pressure calculation with range normalization
Volume-weighted analysis with capping
Multi-factor momentum scoring system
WaveTrend oscillator integration
Energy wave calculation combining multiple sources
Sophisticated divergence detection with thresholds
State classification with multiple dimensions
Multi-layer visualization with glow effects
Real-time dashboard with 10 key metrics
Alert conditions for all major pressure events
The code uses confirmed bars for all calculations to prevent repainting.
Originality Statement
This indicator is original in its comprehensive approach to pressure and momentum analysis. While individual components (RSI, MACD, WaveTrend) are established tools, this indicator is justified because:
It synthesizes pressure analysis with volume weighting for more accurate signals
The energy wave concept combines multiple momentum sources into unified analysis
State classification provides clear, actionable market conditions
Divergence detection includes threshold filtering for higher quality signals
Multi-layer visualization with glow effects enhances readability
The dashboard presents complex pressure dynamics in an accessible format
Volume-weighted pressure adds confirmation often missing from momentum indicators
Acceleration analysis provides early warning of momentum shifts
Export functions enable integration with any trading system
Each component provides unique insights: pressure shows force, volume shows participation, momentum shows direction, energy shows power, and divergence shows potential reversals
The indicator's value lies in measuring the underlying forces that drive price movements rather than just tracking price itself, providing traders with deeper insight into market dynamics and potential future direction.
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. Pressure and momentum analysis is a tool for understanding market forces, not a prediction system.
Pressure and momentum can change suddenly due to news events, economic data, or changes in market sentiment. Extreme pressure states can persist longer than expected, and divergences can fail without warning. 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 your account and risk tolerance. Never trade against strong pressure without confirmation - the trend can remain in force longer than your account can survive.
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
SMT Divergence Strength Index [Metrify]This indicator detects SMT-style divergence between the chart symbol and a user-defined reference symbol, then filters those divergence events using a statistical strength condition. The goal is to separate ordinary pivot mismatches from divergence events that occur during unusually large relative movement between the two instruments.
It combines three components in one script: pivot-based divergence detection, Z-score normalization of momentum spread, and a correlation plot for context. The output is an oscillator panel (Z-score columns + correlation line) plus optional SMT labels/lines drawn on the main chart.
SMT divergence logic (structural layer)
The structural part of the script is based on confirmed pivots on the main symbol.
For bearish SMT detection, the script checks whether the main symbol forms a higher high while the reference symbol (evaluated at the same pivot event point) forms a lower high relative to the previous corresponding pivot event. For bullish SMT detection, it checks whether the main symbol forms a lower low while the reference symbol forms a higher low
Reference symbol and inversion
The Reference Symbol (Pairing) input defines the market used for comparison. The usefulness of the divergence output depends heavily on this pairing. The script assumes the comparison is meaningful enough that non-confirmation between the two symbols can be interpreted as a potential imbalance or relative weakness/strength event.
The 'Invert Correlation' option transforms the reference data by using reciprocal values before the divergence and correlation calculations. This can be used when analyzing pairs that are expected to move inversely (like alt to btc in specific event), so the comparison orientation better matches the intended relationship.
Invert Correlation mode (what it does and why it exists)
The Invert Correlation option changes how the reference symbol is transformed before all downstream calculations (pivot comparison, momentum spread, Z-score, and correlation plot). When enabled, the script does not compare the main symbol to the raw reference prices. Instead, it compares against the reciprocal form of the reference series:
reference high is transformed using 1 / low
reference low is transformed using 1 / high
reference close is transformed using 1 / close
This inversion is used so that an inversely related market can be analyzed in the same directional framework as a positively correlated one. In practical terms, it converts an opposite direction relationship into a comparable orientation for SMT logic. After inversion, moves that would normally appear opposite can be interpreted as if they were aligned, allowing the same higher-high / lower-high and lower-low / higher-low SMT structure rules to be applied consistently.
Conceptually, invert mode is useful when your reference asset is expected to move opposite to the main asset and you want the script to evaluate non-confirmation in a unified SMT framework. It does not automatically improve signal quality, but simply changes the orientation of the comparison so the divergence logic matches the relationship you are trying to study.
Use normal mode when the pair is usually expected to move in the same direction.
Use invert mode when the pair is usually expected to move in opposite directions (or when your analysis framework treats one as a risk-off mirror of the other).
Good inversion-pair examples (practical)
1) Risk asset vs Dollar Index (DXY)
This is one of the cleanest concepts for inversion.
BTCUSD vs DXY
ETHUSD vs DXY
OIL VS DXY
NASDAQ (NDX / US100) vs DXY
Gold vs DXY (often inverse, but can break regime)
When DXY rises, risk assets often weaken. Inverting DXY makes the reference move in the same orientation as the risk asset.
2) Equity index vs VIX
Very common inverse relationship idea.
SPX / ES / NQ vs VIX
BTC (sometimes) vs VIX as a broader risk proxy (less direct, more regime dependent)
Why inversion helps: VIX is typically "fear up when equities down". Inverted VIX can be used as a proxy for risk-on alignment.
3) USD-quoted asset vs USD strength proxy
If your main symbol is sensitive to USD strength:
XAUUSD vs DXY
EURUSD vs DXY
GBPUSD vs DXY
AUDUSD vs DXY
These are classic macro pairings where inversion often makes analytical sense.
4) Some commodity currencies vs commodity / dollar drivers (case-by-case)
Examples can work, but are more conditional:
USDCAD vs Oil (WTI) (often inverse-ish relationship via CAD/oil linkage)
AUDUSD vs Copper (sometimes)
NZDUSD vs risk proxy
These are not as stable as DXY/VIX examples, so you need to monitor correlation more carefully.
Trigger conditions in plain terms
A bearish SMT label appears only when all required conditions are satisfied:
a confirmed pivot high exists on the main symbol,
the current main pivot high is higher than the previous main pivot high,
the aligned reference high at the same pivot event is lower than its previous aligned reference high,
and the Z-score condition exceeds the configured threshold.
A bullish SMT label follows the mirrored condition/vice versa.
Display behavior and non-repaint option
The indicator uses confirmed pivots, so signals are known only after pivot confirmation. The Non repaint mode setting controls how labels are displayed:
Enabled: labels are shown on the trigger/confirmation bar (the bar where the pivot is confirmed and the signal becomes true).
Disabled: labels are shifted back to the pivot bar for visual alignment.
This setting affects visualization only. It does not change the underlying pivot confirmation process.
This indicator marks pivot-based intermarket non-confirmation events that occur during statistically elevated relative dislocation.
Pair selection remains a major source of variation in output quality. Weakly related pairs can produce divergence labels that satisfy the script’s rules but are not analytically useful. Indicator
Flow EngineFlow Engine
Most indicators tell you which direction price is moving. Flow Engine tells you whether to trust it . It does this by combining momentum, volume, trend, and a higher timeframe check all into one pane, plus it draws divergence signals directly on your price chart so you never have to look away.
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WHAT'S ON THE SCREEN
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The Histogram (the bars)
This is the main thing. The height of each bar shows how strong the momentum is. The color tells you the direction — cyan for up, red for down.
The part that makes this different is the opacity . If a bar is bright and vivid, it means big volume is behind that move. If a bar looks faded or ghosted, the move happened on low volume and probably won't last. You can see this instantly without checking a separate volume pane.
Tall vivid cyan bar = strong upward move with real volume behind it
Tall faded cyan bar = price went up but nobody really showed up
Same logic applies on the red side
The OB/OS Line
This line tells you when things are getting stretched too far in one direction.
When it goes above +70 — the move is getting overdone on the upside.
When it drops below -70 — the selloff is getting overdone.
In between — cyan means leaning bullish, red means leaning bearish
The Trend Line
A slow moving line that tells you what the overall structure looks like on your current timeframe.
Lime green above zero — uptrend
Soft red below zero — downtrend
Think of it as the background context. When this line is green, you want to be looking for longs. When it's red, be careful going long or look for shorts instead.
The Background Tint (HTF Bias)
A very subtle color behind everything that comes from a higher timeframe — by default the Daily chart.
Cyan tint — the daily trend is bullish
Red tint — the daily trend is bearish
No tint — daily is mixed, no clear direction
This is the big picture check. If you are trading a 15 minute chart and the background is red, you know you are going against the daily trend. That doesn't mean you can't trade, but you should be more careful.
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DIVERGENCE SIGNALS
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Divergence is when price and momentum stop agreeing with each other. It usually means the current move is running out of steam.
Bearish divergence — price made a higher high but the histogram made a lower high. The rally is weakening. Orange triangle appears above the candle on your price chart.
Bullish divergence — price made a lower low but the histogram made a higher low. The selloff is weakening. Green triangle appears below the candle on your price chart.
You also get a dashed line drawn on the Flow Engine pane connecting the two points so you can see exactly where the divergence happened.
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SETTINGS
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Momentum Length (14) — how many bars the momentum calculation looks back. Lower number reacts quicker but gives more false signals. Higher number is slower but cleaner.
Volume MA Length (20) — the average used to judge whether current volume is high or low. Leave this at default unless you have a reason to change it.
Overbought Level (70) — where the OB/OS line turns orange. Lower this if you want earlier warnings.
Oversold Level (-70) — where the OB/OS line turns green. Change this together with the overbought level.
Trend Length (50) — how slow the trend line moves. Higher number = smoother line.
Pivot Lookback Left & Right (5) — controls how strict the divergence detection is. Raise both to 8 or 10 if you are getting too many signals. Lower to 3 if you want more.
HTF Timeframe (D) — the higher timeframe for the background tint. Set this one step above whatever chart you are on. D = Daily, W = Weekly, 240 = 4 Hour.
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HOW TO USE IT
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Every time you look at the indicator, go through it top to bottom:
Check the background tint — what is the daily (or higher TF) saying?
Check the trend line — is the current chart agreeing with that?
Check the OB/OS line — are we stretched? If yes, don't chase.
Check the histogram — is momentum vivid (real) or faded (weak)?
The best setup looks like this:
Background is cyan + trend line above zero + OB/OS line near oversold + bullish divergence triangle on the chart + histogram bars turning bright cyan
When all of that lines up, the move has multiple things confirming it at the same time. That's when you pay attention.
A quick tip on the faded bars: Don't get excited about a tall bar if it's faded. Price can move fast on thin volume and snap right back. The vivid bars are the ones that tend to follow through.
Which timeframe to set HTF to:
Trading 1m or 5m → set HTF to 1H or 4H
Trading 15m or 1H → keep HTF on Daily
Trading 4H or Daily → set HTF to Weekly
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GOOD TO KNOW
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Does not repaint — signals are based on confirmed bars only
Divergence signals show up a few bars after the actual pivot
Looks best on a dark theme
Indicator
Indicator
Volume HeatMap Divergence [BigBeluga]🔵 OVERVIEW
The Volume HeatMap Divergence is a smart volume visualization tool that overlays normalized volume data directly on the chart. Using a color heatmap from aqua to red, it transforms raw volume into an intuitive scale — highlighting areas of weak to intense market participation. Additionally, it detects volume-based divergences from price to signal potential reversals or exhaustion zones. Combined with clear visual labeling, this tool empowers traders with actionable volume insights.
🔵 CONCEPTS
Normalized Volume Heatmap : Volume is normalized to a 0–100% scale and visually represented as candles below the chart.
float vol = volume / ta.percentile_nearest_rank(volume, 1000, 100) * 100
Bar Coloring : Price candles are dynamically colored based on volume intensity.
Volume Divergence Logic :
Bullish Divergence : Price forms a lower low, but volume forms a higher low.
Bearish Divergence : Price forms a higher high, but volume forms a lower high.
Dynamic Detection Range : Customizable range ensures divergence signals are meaningful and not random.
Volume Labels : Additional info on divergence bars shows both the actual volume and its normalized % score.
🔵 FEATURES
Volume Heatmap Plot : Normalized volume values colored using a smooth gradient from aqua (low) to red (high).
Price Bar Coloring : Candlesticks on the main chart adopt the same heatmap color based on volume.
Divergence Detection :
Bullish divergence with label and low marker
Bearish divergence with label and high marker
Dual Divergence Labels :
On the volume plot : Direction (Bull/Bear), raw volume, and normalized %
On the price chart : Shape labels showing "Bull" or "Bear" at local highs/lows
Custom Inputs :
Divergence range (min & max), pivot detection distance (left/right)
Toggle to show/hide divergence labels, volume, and % text
Clear Bull/Bear Coloring : Fully customizable label and line colors for both bullish and bearish signals.
🔵 HOW TO USE
Use the indicator as an overlay to monitor real-time volume strength using the heatmap color.
Watch for divergence markers:
Bullish divergence: Candle shows higher volume while price makes a new low
Bearish divergence: Candle shows lower volume while price makes a new high
Use the volume info labels to verify the context of divergence:
Actual volume at divergence candle
Normalized % of that volume compared to past 1000 bars
Adjust pivot sensitivity using "Pivot Left" and "Pivot Right" to tune signal frequency and lag with a right pivot length.
Use divergence zones as early warnings for potential reversals or trend shifts.
Disable or customize labels in settings depending on your charting preferences.
🔵 CONCLUSION
Volume HeatMap Divergence merges heatmap-style volume visualization with intelligent divergence detection — giving traders a clean yet powerful edge. By revealing hidden disconnections between price and participation, it helps users spot exhaustion moves or hidden accumulation zones before the market reacts. Whether you’re a scalper, swing trader, or intraday strategist, this tool offers real-time clarity on who’s in control behind the candles. Indicator
Range Oscillator (Zeiierman)█ Overview
Range Oscillator (Zeiierman) is a dynamic market oscillator designed to visualize how far the price is trading relative to its equilibrium range. Instead of relying on traditional overbought/oversold thresholds, it uses adaptive range detection and heatmap coloring to reveal where price is trading within a volatility-adjusted band.
The oscillator maps market movement as a heat zone, highlighting when the price approaches the upper or lower range boundaries and signaling potential breakout or mean-reversion conditions.
Highlights
Adaptive range detection based on ATR and weighted price movement.
Heatmap-driven coloring that visualizes volatility pressure and directional bias.
Clear transition zones for detecting trend shifts and equilibrium points.
█ How It Works
⚪ Range Detection
The indicator identifies a dynamic price range using two main parameters:
Minimum Range Length: The number of bars required to confirm that a valid range exists.
Range Width Multiplier: Expands or contracts the detected range proportionally to the ATR (Average True Range).
This approach ensures that the oscillator automatically adapts to both trending and ranging markets without manual recalibration.
⚪ Weighted Mean Calculation
Instead of a simple moving average, the script calculates a weighted equilibrium mean based on the size of consecutive candle movements:
Larger price changes are given greater weight, emphasizing recent volatility.
⚪ Oscillator Formula
Once the range and equilibrium mean are defined, the oscillator computes:
Osc = 100 * (Close - Mean) / RangeATR
This normalizes price distance relative to the dynamic range size — producing consistent readings across volatile and quiet periods.
█ Heatmap Logic
The Range Oscillator includes a built-in heatmap engine that color-codes each oscillator value based on recent price interaction intensity:
Strong Bullish Zones: Bright green — price faces little resistance upward.
Weak Bullish Zones: Muted green — uptrend continuation but with minor hesitation.
Transition Zones: Blue — areas of uncertainty or trend shift.
Weak Bearish Zones: Maroon — downtrend pressure but soft momentum.
Strong Bearish Zones: Bright red — strong downside continuation with low resistance.
Each color band adapts dynamically using:
Number of Heat Levels: Controls granularity of the heatmap.
Minimum Touches per Level: Defines how reactive or “sensitive” each color zone is.
█ How to Use
⚪ Trend & Momentum Confirmation
When the oscillator stays above +0 with green coloring, it suggests sustained bullish pressure.
Similarly, readings below –0 with red coloring, it suggests sustained bearish pressure.
⚪ Range Breakouts
When the oscillator line breaks above +100 or below –100, the price is exceeding its normal volatility range, often signaling breakout potential or exhaustion extremes.
⚪ Mean Reversion Trades
Look for the oscillator to cross back toward zero after reaching an extreme. These transitions (often marked by blue tones) can identify early reversals or range resets.
⚪ Divergence
Use oscillator peaks and troughs relative to price action to spot hidden strength or weakness before the next move.
█ Settings
Minimum Range Length: Number of bars needed to confirm a valid range.
Range Width Multiplier: Expands or contracts range width based on ATR.
Number of Heat Levels: Number of gradient bands used in the oscillator.
Minimum Touches per Level: Sensitivity threshold for when a zone becomes “hot.”
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Disclaimer
The content provided in my scripts, indicators, ideas, algorithms, and systems is for educational and informational purposes only. It does not constitute financial advice, investment recommendations, or a solicitation to buy or sell any financial instruments. 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. Indicator
Divergence Strategy [Trendoscope®]🎲 Overview
The Divergence Strategy is a sophisticated PulseWire strategy that enhances the Divergence Screener by adding automated trade signal generation, risk management, and trade visualization. It leverages the screener’s robust divergence detection to identify bullish, bearish, regular, and hidden divergences, then executes trades with precise entry, stop-loss, and take-profit levels. Designed for traders seeking automated trading solutions, this strategy offers customizable trade parameters and visual feedback to optimize performance across various markets and timeframes.
For core divergence detection features, including oscillator options, trend detection methods, zigzag pivot analysis, and visualization, refer to the Divergence Screener documentation. This description focuses on the strategy-specific enhancements for automated trading and risk management.
🎲 Strategy Features
🎯Automated Trade Signal Generation
Trade Direction Control : Restrict trades to long-only or short-only to align with market bias or strategy goals, preventing conflicting orders.
Divergence Type Selection : Choose to trade regular divergences (bullish/bearish), hidden divergences, or both, targeting reversals or trend continuations.
Entry Type Options :
Cautious : Enters conservatively at pivot points and exits quickly to minimize risk exposure.
Confident : Enters aggressively at the latest price and holds longer to capture larger moves.
Mixed : Combines conservative entries with delayed exits for a balanced approach.
Market vs. Stop Orders: Opt for market orders for instant execution or stop orders for precise price entry.
🎯 Enhanced Risk Management
Risk/Reward Ratio : Define a risk-reward ratio (default: 2.0) to set profit targets relative to stop-loss levels, ensuring consistent trade sizing.
Bracket Orders : Trades include entry, stop-loss, and take-profit levels calculated from divergence pivot points, tailored to the entry type and risk-reward settings.
Stop-Loss Placement : Stops are strategically set (e.g., at recent pivot or last price point) based on entry type, balancing risk and trade validity.
Order Cancellation : Optionally cancel pending orders when a divergence is broken (e.g., price moves past the pivot in the wrong direction), reducing invalid trades. This feature is toggleable for flexibility.
🎯 Trade Visualization
Target and Stop Boxes : Displays take-profit (lime) and stop-loss (orange) levels as boxes on the price chart, extending 10 bars forward for clear visibility.
Dynamic Trade Updates : Trade visualizations are added, updated, or removed as trades are executed, canceled, or invalidated, ensuring accurate feedback.
Overlay Integration : Trade levels overlay the price chart, complementing the screener’s oscillator-based divergence lines and labels.
🎯 Strategy Default Configuration
Capital and Sizing : Set initial capital (default: $1,000,000) and position size (default: 20% of equity) for realistic backtesting.
Pyramiding : Allows up to 4 concurrent trades, enabling multiple divergence-based entries in trending markets.
Commission and Margin : Accounts for commission (default: 0.01%) and margin (100% for long/short) to reflect trading costs.
Performance Optimization : Processes up to 5,000 bars dynamically, balancing historical analysis and real-time execution.
🎲 Inputs and Configuration
🎯Trade Settings
Direction : Select Long or Short (default: Long).
Divergence : Trade Regular, Hidden, or Both divergence types (default: Both).
Entry/Exit Type : Choose Cautious, Confident, or Mixed (default: Cautious).
Risk/Reward : Set the risk-reward ratio for profit targets (default: 2.0).
Use Market Order : Enable market orders for immediate entry (default: false, uses limit orders).
Cancel On Break : Cancel pending orders when divergence is broken (default: true).
🎯Inherited Settings
The strategy inherits all inputs from the Divergence Screener, including:
Oscillator Settings : Oscillator type (e.g., RSI, CCI), length, and external oscillator option.
Trend Settings : Trend detection method (Zigzag, MA Difference, External), MA type, and length.
Zigzag Settings : Zigzag length (fixed repaint = true).
🎲 Entry/Exit Types for Divergence Scenarios
The Divergence Strategy offers three Entry/Exit Type options—Cautious, Confident, and Mixed—which determine how trades are entered and exited based on divergence pivot points. This section explains how these settings apply to different divergence scenarios, with placeholders for screenshots to illustrate each case.
The divergence pattern forms after 3 pivots. The stop and entry levels are formed on one of these levels based on Entry/Exit types.
🎯Bullish Divergence (Reversal)
A bullish divergence occurs when price forms a lower low, but the oscillator forms a higher low, signaling a potential upward reversal.
💎 Cautious:
Entry : At the pivot high point for a conservative entry.
Exit : Stop-loss at the last pivot point (previous low that is higher than the current pivot low); take-profit at risk-reward ratio. Canceled if price breaks below the pivot (if Cancel On Break is enabled).
Behavior : Enters after confirmation and exits quickly to limit downside risk.
💎Confident:
Entry : At the last pivot low, (previous low which is higher than the current pivot low) for an aggressive entry.
Exit : Stop-loss at recent pivot low, which is the lowest point; take-profit at risk-reward ratio. Canceled if price breaks below the pivot. (lazy exit)
Behavior : Enters early to capture trend continuation, holding longer for gains.
💎Mixed:
Entry : At the pivot high point (conservative).
Exit : Stop-loss at the recent pivot point that has resulted in lower low (lazy exit). Canceled if price breaks below the pivot.
Behavior : Balances entry caution with extended holding for trend continuation.
🎯Bearish Divergence (Reversal)
A bearish divergence occurs when price forms a higher high, but the oscillator forms a lower high, indicating a potential downward reversal.
💎Cautious:
Entry : At the pivot low point (lower high) for a conservative short entry.
Exit : Stop-loss at the previous pivot high point (previous high); take-profit at risk-reward ratio. Canceled if price breaks above the pivot (if Cancel On Break is enabled).
Behavior : Enters conservatively and exits quickly to minimize risk.
💎Confident:
Entry : At the last price point (previous high) for an aggressive short entry.
Exit : Stop-loss at the pivot point; take-profit at risk-reward ratio. Canceled if price breaks above the pivot.
Behavior : Enters early to maximize trend continuation, holding longer.
💎Mixed:
Entry : At the previous piot high point (conservative).
Exit : Stop-loss at the last price point (delayed exit). Canceled if price breaks above the pivot.
Behavior : Combines conservative entry with extended holding for downtrend gains.
🎯Bullish Hidden Divergence (Continuation)
A bullish hidden divergence occurs when price forms a higher low, but the oscillator forms a lower low, suggesting uptrend continuation. In case of Hidden bullish divergence, b]Entry is always on the previous pivot high (unless it is a market order)
💎Cautious:
Exit : Stop-loss at the recent pivot low point (higher than previous pivot low); take-profit at risk-reward ratio. Canceled if price breaks below the pivot (if Cancel On Break is enabled).
Behavior : Enters after confirmation and exits quickly to limit downside risk.
💎Confident:
Exit : Stop-loss at previous pivot low, which is the lowest point; take-profit at risk-reward ratio. Canceled if price breaks below the pivot. (lazy exit)
Behavior : Enters early to capture trend continuation, holding longer for gains.
🎯Bearish Hidden Divergence (Continuation)
A bearish hidden divergence occurs when price forms a lower high, but the oscillator forms a higher high, suggesting downtrend continuation. In case of Hidden Bearish divergence, b]Entry is always on the previous pivot low (unless it is a market order)
💎Cautious:
Exit : Stop-loss at the latest pivot high point (which is a lower high); take-profit at risk-reward ratio. Canceled if price breaks above the pivot (if Cancel On Break is enabled).
Behavior : Enters conservatively and exits quickly to minimize risk.
💎Confident/Mixed:
Exit : Stop-loss at the previous pivot high point; take-profit at risk-reward ratio. Canceled if price breaks above the pivot.
Behavior : Uses the late exit point to hold longer.
🎲 Usage Instructions
🎯Add to Chart:
Add the Divergence Strategy to your PulseWire chart.
The oscillator and divergence signals appear in a separate pane, with trade levels (target/stop boxes) overlaid on the price chart.
🎯Configure Settings:
Adjust trade settings (direction, divergence type, entry type, risk-reward, market orders, cancel on break).
Modify inherited Divergence Screener settings (oscillator, trend method, zigzag length) as needed.
Enable/disable alerts for divergence notifications.
🎯Interpret Signals:
Long Trades: Triggered on bullish or bullish hidden divergences (if allowed), shown with green/lime lines and labels.
Short Trades: Triggered on bearish or bearish hidden divergences (if allowed), shown with red/orange lines and labels.
Monitor lime (target) and orange (stop) boxes for trade levels.
Review strategy performance metrics (e.g., profit/loss, win rate) in the strategy tester.
🎯Backtest and Optimize:
Use PulseWire’s strategy tester to evaluate performance on historical data.
Fine-tune risk-reward, entry type, position sizing, and cancellation settings to suit your market and timeframe.
For questions, suggestions, or support, contact Trendoscope via PulseWire or official support channels. Stay tuned for updates and enhancements to the Divergence Strategy! Strategy
Quarterly Theory ICT 04 [TradingFinder] SSMT 4Quarter Divergence🔵 Introduction
Sequential SMT Divergence is an advanced price-action-based analytical technique rooted in the ICT (Inner Circle Trader) methodology. Its primary objective is to identify early-stage divergences between correlated assets within precise time structures. This tool not only breaks down market structure but also enables traders to detect engineered liquidity traps before the market reacts.
In simple terms, SMT (Smart Money Technique) occurs when two correlated assets—such as indices (ES and NQ), currency pairs (EURUSD and GBPUSD), or commodities (Gold and Silver)—exhibit different reactions at key price levels (swing highs or lows). This lack of alignment is often a sign of smart money manipulation and signals a lack of confirmation in the ongoing trend—hinting at an imminent reversal or at least a pause in momentum.
In its Sequential form, SMT divergences are examined through a more granular temporal lens—between intraday quarters (Q1 through Q4). When SMT appears at the transition from one quarter to another (e.g., Q1 to Q2 or Q3 to Q4), the signal becomes significantly more powerful, often aligning with a critical phase in the Quarterly Theory—a framework that segments market behavior into four distinct phases: Accumulation, Manipulation, Distribution, and Reversal/Continuation.
For instance, a Bullish SMT forms when one asset prints a new low while its correlated counterpart fails to break the corresponding low from the previous quarter. This usually indicates absorption of selling pressure and the beginning of accumulation by smart money. Conversely, a Bearish SMT arises when one asset makes a higher high, but the second asset fails to confirm, signaling distribution or a fake-out before a decline.
However, SMT alone is not enough. To confirm a true Market Structure Break (MSB), the appearance of a Precision Swing Point (PSP) is essential—a specific candlestick formation on a lower timeframe (typically 5 to 15 minutes) that reveals the entry of institutional participants. The combination of SMT and PSP provides a more accurate entry point and better understanding of premium and discount zones.
The Sequential SMT Indicator, introduced in this article, dynamically scans charts for such divergence patterns across multiple sessions. It is applicable to various markets including Forex, crypto, commodities, and indices, and shows particularly strong performance during mid-week sessions (Wednesdays and Thursdays)—when most weekly highs and lows tend to form.
Bullish Sequential SMT :
Bearish Sequential SMT :
🔵 How to Use
The Sequential SMT (SSMT) indicator is designed to detect time and structure-based divergences between two correlated assets. This divergence occurs when both assets print a similar swing (high or low) in the previous quarter (e.g., Q3), but in the current quarter (e.g., Q4), only one asset manages to break that swing level—while the other fails to reach it.
This temporal mismatch is precisely identified by the SSMT indicator and often signals smart money activity, a market phase transition, or even the presence of an engineered liquidity trap. The signal becomes especially powerful when paired with a Precision Swing Point (PSP)—a confirming candle on lower timeframes (5m–15m) that typically indicates a market structure break (MSB) and the entry of smart liquidity.
🟣 Bullish Sequential SMT
In the previous quarter, both assets form a similar swing low.
In the current quarter, one asset (e.g., EURUSD) breaks that low and trades below it.
The other asset (e.g., GBPUSD) fails to reach the same low, preserving the structure.
This time-based divergence reflects declining selling pressure, potential absorption, and often marks the end of a manipulation phase and the start of accumulation. If confirmed by a bullish PSP candle, it offers a strong long opportunity, with stop-losses defined just below the swing low.
🟣 Bearish Sequential SMT
In the previous quarter, both assets form a similar swing high.
In the current quarter, one asset (e.g., NQ) breaks above that high.
The other asset (e.g., ES) fails to reach that high, remaining below it.
This type of divergence signals weakening bullish momentum and the likelihood of distribution or a fake-out before a price drop. When followed by a bearish PSP candle, it sets up a strong shorting opportunity with targets in the discount zone and protective stops placed above the swing high.
🔵 Settings
⚙️ Logical Settings
Quarterly Cycles Type : Select the time segmentation method for SMT analysis.
Available modes include: Yearly, Monthly, Weekly, Daily, 90 Minute, and Micro.
These define how the indicator divides market time into Q1–Q4 cycles.
Symbol : Choose the secondary asset to compare with the main chart asset (e.g., XAUUSD, US100, GBPUSD).
Pivot Period : Sets the sensitivity of the pivot detection algorithm. A smaller value increases responsiveness to price swings.
Activate Max Pivot Back : When enabled, limits the maximum number of past pivots to be considered for divergence detection.
Max Pivot Back Length : Defines how many past pivots can be used (if the above toggle is active).
Pivot Sync Threshold : The maximum allowed difference (in bars) between pivots of the two assets for them to be compared.
Validity Pivot Length : Defines the time window (in bars) during which a divergence remains valid before it's considered outdated.
🎨 Display Settings
Show Cycle :Toggles the visual display of the current Quarter (Q1 to Q4) based on the selected time segmentation
Show Cycle Label : Shows the name (e.g., "Q2") of each detected Quarter on the chart.
Show Bullish SMT Line : Draws a line connecting the bullish divergence points.
Show Bullish SMT Label : Displays a label on the chart when a bullish divergence is detected.
Bullish Color : Sets the color for bullish SMT markers (label, shape, and line).
Show Bearish SMT Line : Draws a line for bearish divergence.
Show Bearish SMT Label : Displays a label when a bearish SMT divergence is found.
Bearish Color : Sets the color for bearish SMT visual elements.
🔔 Alert Settings
Alert Name : Custom name for the alert messages (used in PulseWire’s alert system).
Message Frequency :
All: Every signal triggers an alert.
Once Per Bar: Alerts once per bar regardless of how many signals occur.
Per Bar Close: Only triggers when the bar closes and the signal still exists.
Time Zone Display : Choose the time zone in which alert timestamps are displayed (e.g., UTC).
Bullish SMT Divergence Alert : Enable/disable alerts specifically for bullish signals.
Bearish SMT Divergence Alert : Enable/disable alerts specifically for bearish signals
🔵 Conclusion
The Sequential SMT (SSMT) indicator is a powerful and precise tool for identifying structural divergences between correlated assets within a time-based framework. Unlike traditional divergence models that rely solely on sequential pivot comparisons, SSMT leverages Quarterly Theory, in combination with concepts like liquidity sweeps, market structure breaks (MSB) and precision swing points (PSP), to provide a deeper and more actionable view of market dynamics.
By using SSMT, traders gain not only the ability to identify where divergence occurs, but also when it matters most within the market cycle. This empowers them to anticipate major moves or traps before they fully materialize, and position themselves accordingly in high-probability trade zones.
Whether you're trading Forex, crypto, indices, or commodities, the true strength of this indicator is revealed when used in sync with the Accumulation, Manipulation, Distribution, and Reversal phases of the market. Integrated with other confluence tools and market models, SSMT can serve as a core component in a professional, rule-based, and highly personalized trading strategy.
Indicator
Awesome Oscillator (AO) with Signals [AIBitcoinTrend]👽 Multi-Scale Awesome Oscillator (AO) with Signals (AIBitcoinTrend)
The Multi-Scale Awesome Oscillator transforms the traditional Awesome Oscillator (AO) by integrating multi-scale wavelet filtering, enhancing its ability to detect momentum shifts while maintaining responsiveness across different market conditions.
Unlike conventional AO calculations, this advanced version refines trend structures using high-frequency, medium-frequency, and low-frequency wavelet components, providing traders with superior clarity and adaptability.
Additionally, it features real-time divergence detection and an ATR-based dynamic trailing stop, making it a powerful tool for momentum analysis, reversals, and breakout strategies.
👽 What Makes the Multi-Scale AO – Wavelet-Enhanced Momentum Unique?
Unlike traditional AO indicators, this enhanced version leverages wavelet-based decomposition and volatility-adjusted normalization, ensuring improved signal consistency across various timeframes and assets.
✅ Wavelet Smoothing – Multi-Scale Extraction – Captures short-term fluctuations while preserving broader trend structures.
✅ Frequency-Based Detail Weights – Separates high, medium, and low-frequency components to reduce noise and improve trend clarity.
✅ Real-Time Divergence Detection – Identifies bullish and bearish divergences for early trend reversals.
✅ Crossovers & ATR-Based Trailing Stops – Implements intelligent trade management with adaptive stop-loss levels.
👽 The Math Behind the Indicator
👾 Wavelet-Based AO Smoothing
The indicator applies multi-scale wavelet decomposition to extract high-frequency, medium-frequency, and low-frequency trend components, ensuring an optimal balance between reactivity and smoothness.
sma1 = ta.sma(signal, waveletPeriod1)
sma2 = ta.sma(signal, waveletPeriod2)
sma3 = ta.sma(signal, waveletPeriod3)
detail1 = signal - sma1 // High-frequency detail
detail2 = sma1 - sma2 // Intermediate detail
detail3 = sma2 - sma3 // Low-frequency detail
advancedAO = weightDetail1 * detail1 + weightDetail2 * detail2 + weightDetail3 * detail3
Why It Works:
Short-Term Smoothing: Captures rapid fluctuations while minimizing noise.
Medium-Term Smoothing: Balances short-term and long-term trends.
Long-Term Smoothing: Enhances trend stability and reduces false signals.
👾 Z-Score Normalization
To ensure consistency across different markets, the Awesome Oscillator is normalized using a Z-score transformation, making overbought and oversold levels stable across all assets.
normFactor = ta.stdev(advancedAO, normPeriod)
normalizedAO = advancedAO / nz(normFactor, 1)
Why It Works:
Standardizes AO values for comparison across assets.
Enhances signal reliability, preventing misleading spikes.
👽 How Traders Can Use This Indicator
👾 Divergence Trading Strategy
Bullish Divergence
Price makes a lower low, while AO forms a higher low.
A buy signal is confirmed when AO starts rising.
Bearish Divergence
Price makes a higher high, while AO forms a lower high.
A sell signal is confirmed when AO starts declining.
👾 Buy & Sell Signals with Trailing Stop
Bullish Setup:
✅AO crosses above the bullish trigger level → Buy Signal.
✅Trailing stop placed at Low - (ATR × Multiplier).
✅Exit if price crosses below the stop.
Bearish Setup:
✅AO crosses below the bearish trigger level → Sell Signal.
✅Trailing stop placed at High + (ATR × Multiplier).
✅Exit if price crosses above the stop.
👽 Why It’s Useful for Traders
Wavelet-Enhanced Filtering – Retains essential trend details while eliminating excessive noise.
Multi-Scale Momentum Analysis – Separates different trend frequencies for enhanced clarity.
Real-Time Divergence Alerts – Identifies early reversal signals for better entries and exits.
ATR-Based Risk Management – Ensures stops dynamically adapt to market conditions.
Works Across Markets & Timeframes – Suitable for stocks, forex, crypto, and futures trading.
👽 Indicator Settings
AO Short Period – Defines the short-term moving average for AO calculation.
AO Long Period – Defines the long-term moving average for AO smoothing.
Wavelet Smoothing – Adjusts multi-scale decomposition for different market conditions.
Divergence Detection – Enables or disables real-time divergence analysis. Normalization Period – Sets the lookback period for standard deviation-based AO normalization.
Cross Signals Sensitivity – Controls crossover signal strength for buy/sell signals.
ATR Trailing Stop Multiplier – Adjusts the sensitivity of the trailing stop.
Disclaimer: This indicator is designed for educational purposes and does not constitute financial advice. Please consult a qualified financial advisor before making investment decisions.
Indicator
Divergence IQ [TradingIQ]Hello Traders!
Introducing "Divergence IQ"
Divergence IQ lets traders identify divergences between price action and almost ANY PulseWire technical indicator. This tool is designed to help you spot potential trend reversals and continuation patterns with a range of configurable features.
Features
Divergence Detection
Detects both regular and hidden divergences for bullish and bearish setups by comparing price movements with changes in the indicator.
Offers two detection methods: one based on classic pivot point analysis and another that provides immediate divergence signals.
Option to use closing prices for divergence detection, allowing you to choose the data that best fits your strategy.
Normalization Options:
Includes multiple normalization techniques such as robust scaling, rolling Z-score, rolling min-max, or no normalization at all.
Adjustable normalization window lets you customize the indicator to suit various market conditions.
Option to display the normalized indicator on the chart for clearer visual comparison.
Allows traders to take indicators that aren't oscillators, and convert them into an oscillator - allowing for better divergence detection.
Simulated Trade Management:
Integrates simulated trade entries and exits based on divergence signals to demonstrate potential trading outcomes.
Customizable exit strategies with options for ATR-based or percentage-based stop loss and profit target settings.
Automatically calculates key trade metrics such as profit percentage, win rate, profit factor, and total trade count.
Visual Enhancements and On-Chart Displays:
Color-coded signals differentiate between bullish, bearish, hidden bullish, and hidden bearish divergence setups.
On-chart labels, lines, and gradient flow visualizations clearly mark divergence signals, entry points, and exit levels.
Configurable settings let you choose whether to display divergence signals on the price chart or in a separate pane.
Performance Metrics Table:
A performance table dynamically displays important statistics like profit, win rate, profit factor, and number of trades.
This feature offers an at-a-glance assessment of how the divergence-based strategy is performing.
The image above shows Divergence IQ successfully identifying and trading a bullish divergence between an indicator and price action!
The image above shows Divergence IQ successfully identifying and trading a bearish divergence between an indicator and price action!
The image above shows Divergence IQ successfully identifying and trading a hidden bullish divergence between an indicator and price action!
The image above shows Divergence IQ successfully identifying and trading a hidden bearish divergence between an indicator and price action!
The performance table is designed to provide a clear summary of simulated trade results based on divergence setups. You can easily review key metrics to assess the strategy’s effectiveness over different time periods.
Customization and Adaptability
Divergence IQ offers a wide range of configurable settings to tailor the indicator to your personal trading approach. You can adjust the lookback and lookahead periods for pivot detection, select your preferred method for normalization, and modify trade exit parameters to manage risk according to your strategy. The tool’s clear visual elements and comprehensive performance metrics make it a useful addition to your technical analysis toolbox.
The image above shows Divergence IQ identifying divergences between price action and OBV with no normalization technique applied.
While traders can look for divergences between OBV and price, OBV doesn't naturally behave like an oscillator, with no definable upper and lower threshold, OBV can infinitely increase or decrease.
With Divergence IQ's ability to normalize any indicator, traders can normalize non-oscillator technical indicators such as OBV, CVD, MACD, or even a moving average.
In the image above, the "Robust Scaling" normalization technique is selected. Consequently, the output of OBV has changed and is now behaving similar to an oscillator-like technical indicator. This makes spotting divergences between the indicator and price easier and more appropriate.
The three normalization techniques included will change the indicator's final output to be more compatible with divergence detection.
This feature can be used with almost any technical indicator.
Stop Type
Traders can select between ATR based profit targets and stop losses, or percentage based profit targets and stop losses.
The image above shows options for the feature.
Divergence Detection Method
A natural pitfall of divergence trading is that it generally takes several bars to "confirm" a divergence. This makes trading the divergence complicated, because the entry at time of the divergence might look great; however, the divergence wasn't actually signaled until several bars later.
To circumvent this issue, Divergence IQ offers two divergence detection mechanisms.
Pivot Detection
Pivot detection mode is the same as almost every divergence indicator on PulseWire. The Pivots High Low indicator is used to detect market/indicator highs and lows and, consequently, divergences.
This method generally finds the "best looking" divergences, but will always take additional time to confirm the divergence.
Immediate Detection
Immediate detection mode attempts to reduce lag between the divergence and its confirmation to as little as possible while avoiding repainting.
Immediate detection mode still uses the Pivots Detection model to find the first high/low of a divergence. However, the most recent high/low does not utilize the Pivot Detection model, and instead immediately looks for a divergence between price and an indicator.
Immediate Detection Mode will always signal a divergence one bar after it's occurred, and traders can set alerts in this mode to be alerted as soon as the divergence occurs.
PulseWire Backtester Integration
Divergence IQ is fully compatible with the PulseWire backtester!
Divergence IQ isn’t designed to be a “profitable strategy” for users to trade. Instead, the intention of including the backtester is to let users backtest divergence-based trading strategies between the asset on their chart and almost any technical indicator, and to see if divergences have any predictive utility in that market.
So while the backtester is available in Divergence IQ, it’s for users to personally figure out if they should consider a divergence an actionable insight, and not a solicitation that Divergence IQ is a profitable trading strategy. Divergence IQ should be thought of as a Divergence backtesting toolkit, not a full-feature trading strategy.
Strategy Properties Used For Backtest
Initial Capital: $1000 - a realistic amount of starting capital that will resonate with many traders
Amount Per Trade: 5% of equity - a realistic amount of capital to invest relative to portfolio size
Commission: 0.02% - a conservative amount of commission to pay for trade that is standard in crypto trading, and very high for other markets.
Slippage: 1 tick - appropriate for liquid markets, but must be increased in markets with low activity.
Once more, the backtester is meant for traders to personally figure out if divergences are actionable trading signals on the market they wish to trade with the indicator they wish to use.
And that's all!
If you have any cool features you think can benefit Divergence IQ - please feel free to share them!
Thank you so much PulseWire community! Strategy
Gufran - Volume DivergenceThis indicator detects bullish and bearish divergences by analyzing price action, volume trends, and RSI (Relative Strength Index) for added confirmation. It highlights key market reversals or trend continuations by identifying when price movement diverges from volume dynamics, providing traders with actionable insights for entry and exit points.
Key Features:
Divergence Detection:
Bullish Divergence: Price makes a lower low, but volume shows higher lows, signaling potential upward reversals.
Bearish Divergence: Price makes a higher high, but volume shows lower highs, signaling potential downward reversals.
RSI Confirmation:
Bullish Signals: Confirmed when RSI is in the oversold zone.
Bearish Signals: Confirmed when RSI is in the overbought zone (optional relaxation of RSI conditions available).
Normalized Volume Analysis:
Volume is scaled to the price range, ensuring clear and meaningful visualization alongside price action.
Customizable Parameters:
Lookback Period: Define how far back the script looks to identify divergences.
Volume Significance: Adjust the threshold for significant volume movements.
RSI Levels: Fine-tune overbought and oversold thresholds for optimal signal accuracy.
Gap Control: Avoid clutter by setting a minimum number of candles between successive divergence signals.
Clear Visual Representation:
Bullish Divergence: Marked with green labels and connecting lines.
Bearish Divergence: Marked with red labels and connecting lines.
Dotted lines show normalized volume divergence, while solid lines indicate price divergence.
Ideal For:
Traders who rely on volume dynamics to validate price movements.
Those looking for an added layer of confidence using RSI to filter false signals.
Swing and intraday traders aiming to identify market reversal zones or continuation patterns.
Customization Options:
Lookback Period: Adjustable range for detecting highs and lows.
Volume Threshold: Define the multiplier for significant volume changes.
RSI Settings: Tailor overbought/oversold levels to suit your trading style.
Relax RSI Condition: Toggle stricter or more flexible conditions for bearish divergences.
How to Use:
Add the indicator to your chart and configure the parameters to fit the asset and timeframe you are trading.
Look for:
Green “Bullish Div” labels near price lows for potential buying opportunities.
Red “Bearish Div” labels near price highs for potential selling opportunities.
Use this indicator in combination with other tools like support/resistance levels, trendlines, or moving averages for a comprehensive trading strategy.
Disclaimer:
This indicator is a tool for educational purposes and should not be used as a standalone trading signal. Always conduct proper risk management and consider additional technical/fundamental analysis before making trading decisions. Indicator
TechniTrend: Dynamic Pair CorrelationTechniTrend: Dynamic Pair Correlation
Description:
The TechniTrend: Dynamic Pair Correlation is a powerful and versatile indicator designed to track the correlation between two assets—whether cryptocurrencies, indices, or other financial instruments—across multiple timeframes. Understanding correlations can provide deep insights into market behavior, helping traders make informed decisions based on how two assets move in relation to each other.
Key Features:
Customizable Pair Selection: Compare any two assets (e.g., Bitcoin and DXY, Ethereum and SP500) to study how their price movements relate over time.
Multi-Timeframe Analysis: Simultaneously track correlations across different timeframes—standard, lower, and higher—providing a comprehensive view of market dynamics.
Dynamic Color Coding for Correlation Strength: Instantly spot correlations with visually intuitive colors—green for strong positive correlation, red for strong negative correlation, and yellow for neutral.
Heatmap Background: An easy-to-read background color heatmap highlights when correlations hit extreme levels, adding another layer of insight to your charts.
Real-Time Alerts: Get notified when correlations exceed your custom thresholds, signaling opportunities for potential breakouts, reversals, or divergences.
Divergence Detection: Automatically highlight moments when asset prices diverge, offering potential entry/exit points for smart trading decisions.
How to Use:
Asset Pair Comparison: Select two symbols to analyze their price correlation, such as BTC/USDT and DXY, or any other pair that fits your strategy.
Set Your Timeframes: Customize your standard, lower, and higher timeframes to monitor correlations at different intervals, allowing you to capture both short-term and long-term relationships.
Track Correlation Strength: Use dynamic color coding to quickly see how closely two assets are moving together. Strong correlations (positive or negative) could signal potential opportunities, while low correlations may indicate the absence of a strong trend.
Utilize Alerts: Receive real-time alerts when correlations cross your predefined thresholds, helping you take action when the market presents strong alignment or divergence.
Divergence Signals: Watch for divergence between the assets on multiple timeframes, which could indicate a potential trend reversal or a shift in market behavior.
Why It’s Essential:
Understanding the relationship between two assets can be a game changer for traders. Whether you're comparing Bitcoin to DXY, tracking the correlation between Ethereum and major indices, or evaluating two cryptocurrencies, this indicator gives you the tools to visualize and respond to market conditions with precision.
Perfect For:
Crypto traders looking to optimize strategies by monitoring the relationship between major cryptocurrencies and other assets.
Arbitrageurs seeking to capitalize on temporary pricing anomalies between correlated pairs.
Trend-followers aiming to catch large movements by detecting alignment or divergence between asset classes.
Portfolio managers monitoring how different asset classes impact each other to hedge or diversify investments.
By leveraging the TechniTrend: Dynamic Pair Correlation indicator, traders can gain deeper insights into market trends, correlations, and divergences, giving them an edge in fast-moving markets. Indicator
Indicator
YD_Divergence_RSI+CMFThe ‘YD_Divergence_RSI+CMF’ indicator can find divergence using RSI (Relative Strength Index) and CMF (Chaikin Money Flow) indicators.
📌 Key functions
1. Search pivot high and pivot low points in a certain length of price.
2. Connect pivot high to pivot high , pivot low to pivot low , forming two standards for divergence in result.
The marker then plots only the higher high, lower low lines.
(higher low and lower high in prices are referred to hidden divergence, which are not considered in this indicator)
3. Compare the two standards with RSI and CMF indicators, send an alert if there is a divergence. As a result, the indicator will find four combination of divergence.
A. Higher high price / Lower RSI (Bearish RSI Divergence)
B. Lower low price / Higher RSI (Bullish RSI Divergence)
C. Higher high price / Lower CMF (Bearish CMF Divergence)
D. Lower low price / Higher CMF (Bullish CMF Divergence)
📌 Details
Developing the indicators, we put a lot of effort in making a customizable and user-friendly interface.
#1. Pivot Setting
Users can set the length to find the pivot high / pivot low in ‘Pivot Settings – Pivot Length.’
Increased pivot Length takes more candles to interpret the chart but reduce false signals since the it uses only the most certain pivot high / pivot low values. Obviously, decreased pivot length will act the opposite.
Users can choose whether to use ‘High/Low’ or ‘Close’ in ‘Pivot Reference’ to set the swing point of prices.
Users can also choose whether to display the pivot high / pivot low marker on the chart.
#2 RSI & CMF Settings
Users can adjust the length of RSI & CMF separately. (The default values are set to 14 and 20 each.)
#3 Label Setting
Users can adjust the text displayed on the chart label. (The default values is set to ‘Bullish / Bearish’, ‘RSI/CMF’, ‘Divergence’.)
Users can reduce the length of text label or simply turn the label off. Just click the ‘Bull/Bear’ or ‘None’ button. ‘Divergence’ works the same.
Users can decide whether to display the ‘Divergence Line and Label’, set custom settings for the label and line. (color, thickness, style, etc)
📌 Alert
Alert are provided as a combination of the chart's symbol and the set label text. For example,
‘BINANCE:BTCUSDT.P, Bullish RSI Divergence’
====================================================
"YD_Divergence_RSI+CMF" 지표 는 RSI와 CMF 지표를 이용해서 Divergence 를 찾아낼 수 있습니다.
📌 주요 기능
1. 정해진 가격 움직임 안에서 pivot high와 pivot low 포인트 를 찾아냅니다.
2. Pivot high로만 이어진 라인과, Pivot low로만 이어진 두 라인을 작도한 뒤 divergence의 기준으로 삼습니다.
이 지표에서는 normal divergence만 사용하기 때문에 차트에 higher high와 lower low만 표기 합니다.
(higher low와 lower high는 hidden divergence로 정의되며, 이 지표에서는 다루지 않습니다.
3. 두 기준선과 RSI, CMF 지표를 각각 비교하고, 결과적으로 4개의 조합을 구할 수 있습니다.
A. Higher high price / Lower RSI (Bearish RSI Divergence)
B. Lower low price / Higher RSI (Bullish RSI Divergence)
C. Higher high price / Lower CMF (Bearish CMF Divergence)
D. Lower low price / Higher CMF (Bullish CMF Divergence)
📌 세부 사항
지표를 개발하며 사용자들이 원하는 방향으로 지표를 설정할 수 있게 작업에 많은 공을 들였습니다. 굉장히 다양한 옵션을 선택할 수 있으며, 원하는 방식으로 지표를 사용할 수 있습니다.
#1 Pivot Setting
Pivot setting에서는 Pivot Length를 변경할 수 있습니다.
Pivot Length를 늘릴 경우, 보다 확실한 Swing High와 Swing Low만을 사용하게 되므로, False signal이 줄어들 수 있습니다. 하지만 Swing High/ Low를 판정하는 데에 더 긴 시간이 걸리게 되므로, Signal이 다소 늦게 발생하는 단점이 생기게 됩니다.
Pivot Length를 줄일 경우, 반대로 Swing High/Low의 판정이 더 빨리 일어나기 때문에, Signal을 거래에 이용하기는 좋을 수 있습니다. 다만, Swing High와 Low가 훨씬 더 잦은 빈도로 발생하기 때문에 False Signal을 줄 가능성이 높아집니다.
Pivot Reference에서는 가격의 Swing Point를 설정함에 있어, High/Low(고가/저가)를 이용할 지 Close (종가)를 이용할 지 선택할 수 있습니다.
Pivot High/Low Marker를 선택할 경우 Pivot High/ Low에 Marker가 찍히게 됩니다.
#2 RSI와 CMF Setting
RSI와 CMF Setting에서는 RSI와 CMF의 길이를 각각 설정할 수 있습니다. 기본값은 14와 20으로 설정되어 있습니다.
#3 Label Setting
Label Setting에서는 Label에 표시되는 글자를 선택할 수 있습니다.
기본값은 "Bullish / Bearish", "RSI/CMF", "Divergence"로 선택되어 있으며, 너무 길다고 느껴질 경우 "Bull/Bear" 혹은 "None"을 클릭하여 길이를 줄일 수 있습니다. 마찬가지로 Divergence의 경우도 생략이 가능합니다.
하단에서는 Divergence Line과 Label을 켜고 끌 수 있으며, 선의 색깔, 굵기, 종류, 그리고 Label의 색깔, 크기, 종류를 선택할 수 있습니다. Label의 Text 색 역시 변경이 가능합니다.
📌 얼러트
얼러트는 자신이 설정한 차트의 심볼과 Label의 문구의 조합으로 제공되며 예를 들면 다음과 같습니다.
"BINANCE:BTCUSDT.P, Bullish RSI Divergence" Indicator
Strategy
Divergence IndicatorDescription:
The Divergence Indicator (DI) is a powerful technical analysis tool designed to identify potential bullish and bearish signals based on multiple indicators, including RSI, Stochastic Oscillator, MACD, and EMA. It helps traders spot divergences between price and these indicators, indicating potential trend reversals or continuations.
How it Works:
The Divergence Indicator compares various indicators and their relationships with price to identify bullish and bearish signals. It considers conditions such as rising or falling values of the Stochastic Oscillator (%K), RSI, and MACD lines, as well as the crossover and crossunder of the MACD Line and Signal Line. Additionally, it evaluates the relationship between fast and slow Exponential Moving Averages (EMA) to detect divergences. When a bullish or bearish condition is met, circles are plotted on the chart to highlight the signals.
Usage:
To effectively utilize the Divergence Indicator, follow these steps:
1. Apply the DI indicator to your chart by adding it from the available indicators.
2. Customize the color settings to suit your preferences. The bullish and bearish colors determine the colors of the plotted circles.
3. Observe the circles plotted on the chart:
- Bullish circles indicate potential bullish signals.
- Bearish circles indicate potential bearish signals.
4. Interpret the signals provided by the indicator:
- A bullish signal may occur when there is price divergence accompanied by rising values of the Stochastic Oscillator (%K), RSI, and MACD lines, or when the MACD Line crosses above the Signal Line. Additionally, a histogram value close to zero may strengthen the signal.
- A bearish signal may occur when there is price divergence accompanied by falling values of the Stochastic Oscillator (%K), RSI, and MACD lines, or when the MACD Line crosses below the Signal Line. A histogram value close to zero may also strengthen the signal.
5. Be cautious of false signals by considering additional factors such as the relationship between the fast and slow Exponential Moving Averages (EMA). If the EMAs or MACD values do not support the identified divergence, the signal may be less reliable.
6. Combine the signals from the Divergence Indicator with other technical analysis tools, such as support and resistance levels, trend lines, or candlestick patterns, to confirm potential trade setups.
7. Implement appropriate risk management strategies, including setting stop-loss orders and position sizing, to manage your trades effectively and protect your capital.
Note: The Divergence Indicator provides valuable insights into potential trend reversals or continuations based on divergences between price and multiple indicators. However, it is recommended to use this indicator in conjunction with other technical analysis tools and perform thorough analysis before making trading decisions. Indicator
