Indicator
Adaptive Cycle Momentum Oscillator [ZurvanEG]⯁ Adaptive Cycle Momentum Oscillator
◇ Overview
MOM is a cycle-adaptive momentum oscillator built to present market direction, strength, fatigue, volatility compression and saturation within one coherent framework.
Unlike conventional momentum oscillators that apply the same lookback to every market condition, MOM can adjust its momentum window to the market’s active rhythm. This allows its response to become faster or slower as market behaviour changes, while a fixed-length mode remains available for users who require consistent settings.
Beyond measuring momentum, MOM adds context to the reading. It distinguishes strengthening movement from fading pressure, reduces the influence of momentum formed during volatility compression, identifies statistically unusual momentum zones, and detects confirmed divergence structures.
The objective is not to produce more signals or predict every reversal. It is to provide a cleaner and more informative view of momentum—showing not only its direction, but also the conditions under which it is developing.
◈ Key Features
◇ Adaptive Momentum
Automatically adjusts the momentum lookback as market rhythm changes. Fixed mode can be selected whenever a constant length is preferred.
◇ Momentum Regime
Classifies momentum as bullish, bearish or neutral. Separate entry and exit levels reduce unstable regime switching around the dead zone.
◇ Strength & Fatigue
The line gradient shows direction and magnitude, while color strength distinguishes expanding momentum from momentum fading toward zero.
◇ Volatility Squeeze
Detects compressed volatility and reduces momentum produced inside quiet conditions. Squeeze intensity can also be displayed as a variable background.
◇ Saturation Bands
Adaptive upper and lower bands identify momentum readings that are extreme relative to the oscillator’s own recent behavior. They should be treated as saturation zones, not automatic reversal signals.
◇ Divergence
Detects confirmed regular and hidden bullish or bearish divergence. Signals can optionally be restricted to pivots occurring beyond the saturation bands to filter weaker mid-range structures.
◇ Visuals & Information
Optional candle coloring transfers the oscillator’s momentum gradient to the main chart. A compact table displays the current regime, momentum value and slope state, with optional cycle, length, squeeze and divergence diagnostics.
◇ Alerts
Independent alerts are available for:
⬦ Bullish and bearish regime shifts
⬦ Upper and lower saturation contacts
⬦ Squeeze entry and release
⬦ Confirmed bullish and bearish divergence
◈ Interpretation
Adaptive Cycle Momentum Oscillator helps answer:
⬦ Is momentum bullish, bearish or neutral?
⬦ Is the current move strengthening or fading?
⬦ Was momentum produced during expansion or compression?
⬦ Is the reading unusually saturated for this market?
⬦ Has a meaningful divergence been confirmed?
◈ Notes
⬦ Adaptive mode requires sufficient historical data for cycle estimation.
⬦ Divergences appear after pivot confirmation and are therefore delayed by design.
⬦ Saturation does not guarantee reversal, especially during strong trends.
⬦ Squeeze attenuation provides context; it does not predict breakout direction.
◈ Conclusion
Adaptive Cycle Momentum Oscillator is designed as a complete momentum-analysis framework rather than a simple oscillator or signal generator. It combines adaptive measurement, stable directional regimes, strength and fatigue colouring, volatility context, dynamic saturation bands and confirmed divergence in a single visual system.
By adapting to market rhythm and evaluating momentum within its surrounding conditions, MOM helps separate meaningful directional pressure from weak movement produced inside noise or compression. Its visual structure is intended to make changes in direction, intensity and exhaustion recognizable without requiring several overlapping indicators.
MOM does not attempt to replace price structure, risk management or trading confirmation. Its role is to provide a clearer and more consistent momentum perspective that can support trend analysis, pullback evaluation, saturation monitoring and divergence assessment across different instruments and timeframes.
Indicator
BTC On-Chain Value Zones [MVRV]BTC Onchain Value Zones (MVRV)
Bitcoin has a cost basis. Realized Price is the average price at which every coin in circulation last moved onchain, which makes it a reasonable proxy for what the average holder actually paid. This script plots that level directly on your price chart and builds valuation zones around it.
MVRV is just price divided by Realized Price. When MVRV falls under 1, the average holder is sitting at a loss. Historically that condition has clustered around cycle lows and long accumulation ranges. When MVRV stretches well above 2.5, the market is carrying a large amount of unrealized profit, and historically that has clustered around distribution phases and cycle highs. It is a slow, structural read, not a trade trigger.
Why I rebuilt it
The common version of this idea relied on the IntoTheBlock MVRV feed. That feed stopped updating in August 2025 and PulseWire flagged it as discontinued. Scripts using it did not throw an error. They quietly froze on a stale value and kept plotting a line that meant nothing, which is worse than breaking outright.
This version calculates MVRV itself from two live feeds:
Realized Price = Realized Cap / Circulating Supply
MVRV = Price / Realized Price
Realized Cap comes from CoinMetrics and Circulating Supply from Glassnode. If either symbol is unavailable on your plan, the script falls back to an alternate ticker automatically. If supply goes dark entirely, it derives supply from market cap divided by price so the realized line keeps working rather than vanishing.
The zones
Deep buy below 0.85, meaning capitulation territory where holders are heavily underwater.
Buy below 1.0, meaning price sits under the aggregate cost basis.
Fair value between 1.0 and 2.5.
Sell above 2.5.
Euphoria above 3.5.
Every threshold is adjustable in settings. The zones are drawn in price terms, not as an oscillator, so you can see exactly what dollar level each multiple sits at right now.
Signals
Markers fire when MVRV crosses a threshold on the daily close. Triangles mark entries into the buy and sell zones, labels mark deep value and euphoria, and a circle marks the moment price reclaims its cost basis, which has historically been a useful bottom confirmation. Alerts are available for each event individually, for any buy event, for any sell event, and for a stale data feed.
Diagnostics
Two tables. The top right shows current MVRV, realized price in dollars, the active zone, how many days old the onchain data is, and which feeds are supplying it. The bottom right lists all six candidate symbols with their current values, marked green if live and red if dead. If a data provider retires a ticker two years from now, you will see it immediately instead of trusting a frozen line.
How to use it
Onchain data updates once per day, so use this on a daily chart or higher. It is built for position sizing and accumulation decisions across weeks and months, not for entries. Treat the zones as context for whatever you are already doing.
One honest caveat. MVRV peaks have declined with every cycle as Bitcoin has matured and the holder base has grown. The 3.5 euphoria level was routine in 2013 and 2017 and has been harder to reach since. Adjust the upper thresholds to fit the market you are actually trading rather than assuming past extremes will repeat.
This is for informational purposes only and is not financial advice. Indicator
Liquidity Thermodynamics Engine V9 LiteLiquidity Thermodynamics Engine V9 Lite is a macro-liquidity oscillator designed to highlight liquidity impulse, acceleration, compression, divergence, and follow-through conditions. It is a lite core version of a more heavy research model that explores liquid thermodynamic phase models as the physics corresponds to capital flows.
The indicator combines major liquidity inputs into a normalized composite, then tracks when liquidity impulse strengthens, compresses, diverges from price, or aligns with acceleration. The Lite version focuses on a clean chart experience while preserving an optional Flow Map for users who want to inspect the underlying liquidity drivers.
Primary signals include:
- Composite and signal line
- Positive and negative impulse histogram
- Bright positive impulse bars
- Acceleration markers
- Compression diamonds
- Bullish and bearish divergence markers
- Bright green follow-through triangle
- Optional energy exhaustion flag
- Optional Flow Map
This tool is intended for macro context and research. It is not financial advice and should not be used as a standalone trading system.
User Guide
Liquidity Thermodynamics Engine V9 Lite, or LTE Lite, is a macro-liquidity momentum oscillator designed to help users visualize when liquidity conditions are compressing, accelerating, diverging from price, or beginning to follow through.
The indicator is not designed to predict every short-term move. It is best used as a higher-timeframe liquidity context tool, especially on slower charts such as the 6D, weekly, or multi-day Bitcoin chart. Its strongest signals tend to come when liquidity impulse and acceleration align near important macro turning zones.
This guide explains what each signal means, how to read the chart, and how to use the tool responsibly.
1. What LTE Lite Measures
LTE Lite combines several macro liquidity series into a normalized oscillator:
- Federal Reserve total assets
- Treasury General Account
- Overnight reverse repo
- Reserve balances
- Optional inverse DXY overlay
The core model converts liquidity conditions into a composite line, then measures the speed and force of changes in that composite. The result is a compact view of liquidity pressure, impulse, acceleration, compression, divergence, and exhaustion.
In simple terms:
- The white line shows the liquidity composite.
- The yellow line smooths that composite into a signal line.
- The histogram shows liquidity impulse.
- Markers highlight important changes in pressure, momentum, divergence, and exhaustion.
2. The Core Lines
White Line — Composite Line
The white line is the main liquidity composite. It represents the current normalized liquidity condition.
When the white line rises, liquidity conditions are generally improving. When it falls, liquidity conditions are generally deteriorating.
The white line is more reactive than the yellow signal line.
Yellow Line — Signal Line
The yellow line is a smoothed version of the composite.
It helps users distinguish noise from directional liquidity movement. When the white line rises above the yellow line, liquidity momentum is improving. When the white line falls below the yellow line, liquidity momentum is weakening.
The signal line is not a trade trigger by itself. It is context.
3. Impulse Histogram
The histogram measures the rate of change in the liquidity composite.
Green Histogram Bars
Green bars show positive liquidity impulse.
This means liquidity pressure is improving relative to the prior bars.
Red Histogram Bars
Red bars show negative liquidity impulse.
This means liquidity pressure is deteriorating.
Bright Green Histogram Bars
Bright green bars mark stronger positive impulse.
By default, LTE Lite highlights positive impulse bars when they reach or exceed the Key Positive Impulse Level. In the current stock configuration, this level is set to `0.10`.
These bars are important because they often mark a stronger liquidity push rather than a minor improvement.
Important: a bright green histogram bar is not automatically a buy signal. Its value increases when it aligns with acceleration, compression release, improving structure, or price confirmation.
4. Acceleration Markers
Acceleration markers show when the impulse itself is accelerating.
Yellow `+`
A yellow plus sign marks positive acceleration.
This means liquidity impulse is not just positive; it is improving quickly enough to clear the acceleration threshold.
Positive acceleration can appear before a larger histogram impulse bar, or the impulse bar can appear first. LTE Lite watches for either order.
Yellow `-`
A yellow minus sign marks negative acceleration.
This means liquidity impulse is weakening quickly.
Negative acceleration can warn that a prior liquidity push is losing force.
5. Bright Green Triangle Signal
The bright green triangle is one of the most important Lite signals.
It fires when:
- A bright positive impulse bar occurs, and
- A positive acceleration signal occurs, and
- The two events happen within the configured window.
The default window is `7` bars.
On a 6D chart, 7 bars is roughly 42 calendar days. This gives the signal room to capture cases where acceleration leads impulse and cases where impulse leads acceleration.
Why This Signal Matters
This signal is designed to identify liquidity follow-through.
The idea is:
- A large positive histogram bar shows meaningful liquidity impulse.
- A `+` acceleration marker shows liquidity momentum is expanding.
- When both appear close together, the market may be entering a more supportive liquidity window.
This does not guarantee immediate upside. It means liquidity conditions have improved enough to deserve attention.
How to Use It
Best practice:
1. Watch for the green triangle on higher timeframes.
2. Check whether price is basing, breaking structure, or reclaiming key levels.
3. Confirm that the composite is stabilizing or rising.
4. Avoid treating the triangle as a standalone entry signal.
The green triangle is a context signal, not a mechanical trading command.
6. Compression Signal
Compression is shown as a small gray diamond around the zero line.
Compression appears when:
- Liquidity impulse is small, and
- Composite movement is also muted, and
- This quiet condition persists for the configured number of bars.
Compression means liquidity energy is coiling.
It does not tell direction by itself. It simply says the system is quiet enough that a larger move may be building.
How to Use Compression
Compression is most useful when followed by:
- Positive acceleration
- Bright green impulse
- A green triangle signal
- Composite reclaiming or curling upward
Compression followed by negative acceleration can instead warn of downside continuation.
7. Divergence Signals
Divergence compares price structure against liquidity structure.
Bullish Divergence
A bullish divergence marker appears when price makes a lower pivot low while the liquidity composite makes a higher pivot low.
This can suggest that price is weakening less efficiently because liquidity conditions are improving underneath the surface.
Bearish Divergence
A bearish divergence marker appears when price makes a higher pivot high while the liquidity composite makes a lower pivot high.
This can suggest that price is rising while liquidity support is weakening.
Divergence Mode
The default mode is:
`Price vs Liquidity + Impulse`
This is stricter than simple price-versus-liquidity divergence because it also checks impulse direction. The goal is to reduce noisy divergence signals.
Divergence is best used as a warning or confirmation tool, not as a standalone entry or exit.
8. Energy Exhaustion Flag
The Energy Exhaustion Flag is an optional marker.
It is designed to identify moments when internal liquidity energy has dropped sharply or clustered into a weak state.
By default in the current V9 Lite stock settings, this marker is turned off.
When enabled, it can help identify late-stage exhaustion after strong liquidity movement. It should be used carefully because exhaustion can persist before price responds.
9. Flow Map
The Flow Map is an optional visual layer.
It breaks liquidity movement into individual components:
- Fed flow
- Treasury flow
- RRP flow
- Reserve flow
The Flow Map helps users see which component is contributing most to liquidity movement.
Flow Map Modes
`Stacked Bars` shows all selected flow components.
`Dominant Bars` shows only the strongest component on each bar.
`Stacked + Dominant Marker` shows the flow bars and adds a marker to the dominant component.
How to Use the Flow Map
Use the Flow Map when you want to inspect what is driving the oscillator.
For example:
- Reserve flow may dominate during banking-system liquidity shifts.
- TGA changes may dominate around Treasury cash rebuilding or drawdowns.
- RRP shifts may dominate when reverse repo usage changes materially.
- Fed balance sheet changes may dominate during major policy/liquidity events.
For clean chart reading, leave Flow Map off. Turn it on when doing deeper diagnostics.
10. Suggested Timeframes
LTE Lite is designed primarily for higher-timeframe liquidity analysis.
Recommended starting points:
- Bitcoin 6D
- Bitcoin weekly
- Major index weekly
- Multi-day charts for macro context
Lower timeframes may produce more noise because macro liquidity data updates slowly relative to intraday price action.
The 6D chart can be especially useful because it balances signal sensitivity with macro smoothness.
11. Practical Reading Workflow
Use this sequence:
Step 1 — Identify the Liquidity Regime
Look at the white and yellow lines.
Is the composite rising, falling, basing, or rolling over?
Step 2 — Check Impulse
Look at the histogram.
Are bars green or red? Are green bars brightening? Is negative impulse fading?
Step 3 — Watch Acceleration
Look for `+` or `-` markers.
A `+` means liquidity momentum is accelerating. A `-` means it is decelerating.
Step 4 — Look for Follow-Through
The green triangle is the key combined signal.
It means strong positive impulse and positive acceleration have occurred within the configured window.
Step 5 — Confirm With Price
Do not use the indicator alone.
Look for price confirmation such as:
- Break of market structure
- Reclaim of key moving averages
- Higher lows
- Range breakout
- Failed breakdown
- Support reclaim
Step 6 — Manage Risk
Liquidity support can improve before price moves. It can also improve while price continues consolidating.
Use invalidation levels, position sizing, and a clear plan.
12. Signal Priority
Not all signals carry equal weight.
Highest priority:
1. Bright green triangle after or near positive acceleration
2. Bright green impulse bars appearing after compression
3. Bullish divergence near a major low
4. Composite rising above the signal line
Medium priority:
1. Positive acceleration without bright impulse
2. Compression alone
3. Flow Map showing improving dominant flow
Lower priority:
1. Small green histogram bars
2. Isolated divergence without impulse confirmation
3. A single marker against strong price downtrend
13. Common Mistakes
Mistake 1 — Treating Every Green Bar as Bullish Enough
Small green bars only show mild improvement. The brighter bars matter more.
Mistake 2 — Ignoring Timeframe
Signals on a 6D or weekly chart are not short-term scalping signals. They describe larger liquidity conditions.
Mistake 3 — Ignoring Price Confirmation
Liquidity can lead price, but price still needs to confirm.
Mistake 4 — Assuming the Triangle Means Immediate Upside
The triangle identifies a supportive liquidity window. It does not guarantee immediate price expansion.
Mistake 5 — Overloading the Chart
Keep Flow Map off unless you are diagnosing components. The cleanest read usually comes from the composite, signal line, histogram, acceleration markers, compression, divergence, and green triangle.
14. Default Settings Philosophy
The stock settings are tuned for a clean macro read.
The defaults prioritize:
- Higher-timeframe stability
- Fewer false signals
- Visibility of major impulse events
- Clean chart presentation
- Optional component diagnostics through Flow Map
If users modify settings, they should do so slowly and test across multiple cycles.
Risk Disclaimer
This indicator is for educational and research purposes only.
It does not provide financial advice, investment advice, or trading recommendations. Markets involve risk, and no indicator can guarantee future performance. Users should combine this tool with independent analysis, risk management, and their own decision-making process.
Past signal behavior does not guarantee future results. Indicator
Bitcoin Halving Cycle Strategy [Gabremoku]This script is a Bitcoin cycle timing indicator built around the historical halving structure.
The core idea is simple:
- define a Buy window a fixed number of days before each halving,
- define a Sell window a fixed number of days after each halving,
- project the next key dates directly on the chart.
The indicator does not try to predict price with oscillators, momentum formulas, or future-looking data. Instead, it focuses on a structural market rhythm that many Bitcoin traders monitor: the recurring supply shock created by halvings.
How it works
- The script uses known historical Bitcoin halving dates.
- It calculates a Buy date at halving minus N days.
- It calculates a Sell date at halving plus N days.
- It draws vertical reference lines for Buy, Halving, and Sell events.
- It plots historical labels on the actual event bars.
- It projects the upcoming Buy, Sell, and Halving labels forward to their own future dates on the chart.
- A dashboard summarizes the active cycle, next key date, and remaining days.
What makes this script useful
Most halving tools only mark the halving date itself. This script expands the concept into a complete cycle timeline by transforming each halving into three practical timing landmarks:
1. accumulation window before halving,
2. halving anchor point,
3. distribution window after halving.
This makes the script more useful for traders and investors who want a visual cycle map instead of a single event marker.
How to use it
- Apply it on BTCUSD or BTCUSDT.
- Daily and weekly charts are the most readable timeframes for this model.
- Use "Buy Days Before Halving" to control how early the accumulation window begins.
- Use "Sell Days After Halving" to control how long the post-halving window extends.
- Use the projected labels to monitor the next cycle dates in advance.
- Use the dashboard to read the current phase quickly.
Included features
- Historical halving timeline
- Buy and Sell event mapping
- Future projected labels positioned on future dates
- Optional cycle range highlighting
- Dashboard with next Buy, next Sell, next Halving, and countdown
- Custom colors and label controls
Important notes
- This script is a cycle visualization tool, not financial advice.
- It does not guarantee future market behavior.
- The projected future halving date is used as a timeline estimate for planning and visualization only.
- Past cycle behavior does not guarantee similar future performance.
- For clarity and to avoid misleading output, this script should be used on standard candlestick charts.
This publication is intended to provide a clean and practical timing framework for Bitcoin traders who study halving-driven market cycles rather than signal-based entry systems. Indicator
Bitcoin Halving Cycle PhasesBitcoin Halving Cycle Phases is a calendar-based visual indicator that highlights approximate Bitcoin halving cycle phase zones directly on the chart.
The indicator uses historical Bitcoin halving dates and predefined calendar phase boundaries to display different cycle regions, including Halving, Bullish, Bearish, Recovery, and Pre-halving phases. Future zones are projected using an approximate cycle length and are intended only as visual calendar references.
This script does not calculate price targets, buy or sell signals, trading entries, exits, stop losses, take profits, backtest results, or financial advice. The displayed future zones are approximate calendar projections only and should not be interpreted as forecasts or guaranteed market outcomes.
The indicator is designed for educational cycle visualization and long-term market context.
Indicator
Dominant Cycle OscillatorDominant Cycle Oscillator
A cycle tool that measures the market's current dominant cycle length directly from the data — rather than assuming a fixed period — then reads where price sits inside that cycle (its phase) and how strong the cycle is (its power). It answers three things a fixed-length oscillator can't: how long the cycle is right now, where we are within it, and whether a tradable cycle even exists.
Why these parts are combined (not a mashup for show). Each is required by the previous one. A band-pass filter isolates the tradable cycle band from slow trend and fast noise — you can't measure a cycle cleanly without first removing what isn't cyclical. An autocorrelation periodogram turns that cleaned series into a power spectrum and reports the dominant period as the spectrum's centre of gravity. A cycle-strength read — how far the dominant peak stands above the spectral noise floor — says whether that period is real or noise, so signals are suppressed when no cycle exists. Forward calibration then measures whether the cycle turns actually pay on this symbol.
How it works. Band-pass (high-pass + low-lag smoother) → autocorrelation across lags → discrete Fourier transform → power spectrum → dominant period via its centre of gravity. The cleaned cycle is normalized into a ±100 phase wave. A long fires when the phase turns up from a trough with a real cycle present, a short when it turns down from a peak; each side fires at most once per swing. Every signal is labelled by a triple barrier — a profit target and equal stop in ATR units plus a time limit — split into in-sample and recent out-of-sample, with a confidence interval and a multiple-testing check.
How to use. Read the Verdict (Long/Short, Weak cycle, or Wait) and the Conviction, which reads "High" only when that turn type shows a positive edge that survives the test on this symbol — otherwise it openly says "context only" or "no proven edge here." The dashboard shows the measured cycle length and its strength. Best used with your own trend and risk plan, not alone.
Honesty & limitations. The dominant-cycle estimate is approximate and lags at regime shifts. Edge figures are computed on this chart's own history with overlapping windows and no costs — context, not a guaranteed backtest; past behaviour doesn't predict the future. Non-repainting. The periodogram is computationally heavy on deep history / very low timeframes.
Disclaimer: for research and education only. Not financial advice. Trading carries risk of loss; manage your own positions. Indicator
Sharp Reversal OscillatorSharp Reversal Oscillator
A reversal-timing oscillator that re-shapes price into a near-Gaussian form so turning points snap into sharp, clear extremes instead of rounded, ambiguous ones — then scores its own turns forward on your chart, in plain language, so you can see at a glance whether to act or wait.
Why these parts are combined (not a mashup for show). Three steps are stacked, each fixing the previous one's flaw. Raw price excursions are fat-tailed, so it's unclear where an extreme really is; a distribution-normalizing transform stretches values near the edges, turning a compressed extreme into a clear spike. But that transform is easily biased by trend — in a strong move it pins to one side — so the input is first band-pass cleaned (slow trend and fastest noise removed), leaving the tradable swing it should sharpen. The normalization window is then set from the market's measured dominant cycle rather than a fixed guess, so it stays tuned as cycles stretch and compress. The three only work as one tool.
How it works. Band-pass clean → locate price within its recent range, scaled to (−1, 1) → distribution-normalizing transform, smoothed → signal when the line crosses its one-bar trigger from an extreme. The window optionally follows a dominant cycle measured by autocorrelation of the band-passed price. Each signal is then labelled by a triple barrier — a profit target and an equal stop in ATR units, plus a time limit — so a "win" means the target was hit before the stop. Results split into in-sample and recent out-of-sample, with a confidence interval and a multiple-testing check.
How to use. Read the Verdict row (Long/Short signal, Watch, or Wait). Check Conviction — it reads "High" only when that signal type shows a positive edge that survives the statistical test on this symbol; otherwise treat it as context. Green wave above zero is up-pressure, red below is down; shaded bands are extremes; the faint line is the trigger. Best used with your own trend and risk plan, not alone.
What's original. The band-pass-cleaned input, the self-tuning window, the forward triple-barrier calibration with an out-of-sample split, and a conviction read that openly admits when there's no proven edge — instead of presenting every signal as equally reliable.
Inputs. Price source (change it for any market), reading mode (Simple/Pro), engine and self-tuning controls, extreme level, full calibration settings, and an auto-adapting dashboard legible on dark or light charts. Defaults are tuned for NSE:NIFTY1! intraday.
Honesty & limitations. Edge figures are computed on this chart's own history with overlapping windows and no costs — context, not a guaranteed backtest; past behaviour doesn't predict the future, and the cycle estimate lags at regime shifts.
Disclaimer: for research and education only. Not financial advice. Trading carries risk of loss; manage your own positions. Indicator
Adaptive Trend Cycle OscillatorAdaptive Trend Cycle Oscillator
A bounded cycle-timing oscillator that does two things most cycle tools don't: it tunes its own period to the market's measured rhythm, and it scores its own signals forward on your chart in plain language — so you can see at a glance whether to act or wait.
What it is. A 0-100-style cycle line (shown −100…+100) that highlights up-phases and down-phases and marks turns out of oversold/overbought. A dashboard translates the current state into a one-word verdict and an honest conviction read.
Why these parts are combined (not a mashup for show). Three classical ideas are fused because each fixes the previous one's flaw. A trend-difference line (fast average minus slow average) captures direction but is unbounded and late at turns. Running it through a double stochastic normalization bounds it and sharpens the cyclical phase, so reversals show sooner with less whipsaw. The remaining weakness is the fixed normalization length — real cycles stretch and compress — so the length is set from a measured dominant cycle (autocorrelation of a band-passed price), making the oscillator self-tuning. The three only work as one tool; separately each is incomplete.
How it works. (1) Dominant cycle: band-pass filter → autocorrelation across lags → Fourier transform → power spectrum → dominant period via its centre of gravity. (2) Oscillator: trend-difference → stochastic over the measured period → smooth → stochastic → smooth. (3) Calibration: each signal is labelled by a triple barrier — a profit target and an equal stop in ATR units, plus a time limit — so a "win" means the target was reached before the stop. Results split into in-sample and recent out-of-sample, with a confidence interval and a multiple-testing check.
How to use. Read the Verdict row first (Long/Short signal, Watch, or Wait). Check Conviction — it only reads "High" when that signal type shows a positive edge that survives the statistical test on this symbol; otherwise treat the signal as context. Green wave above the mid line is an up-phase, red below is a down-phase; shaded bands are extremes. Best used alongside your own trend and risk plan, not alone.
What's original. The self-tuning period, the forward triple-barrier calibration with an out-of-sample split, and a conviction read that openly admits when there's no proven edge — rather than presenting every signal as equally reliable.
Inputs. Price source (change it to use any market), reading mode (Simple/Pro), cycle and self-tuning controls, signal zones, full calibration settings, and an auto-adapting dashboard that stays legible on dark or light charts. Defaults are tuned for NSE:NIFTY1! intraday.
Honesty & limitations. Edge figures are computed on this chart's own history with overlapping windows and no costs — context, not a guaranteed backtest; past behaviour doesn't predict the future, and the cycle estimate lags at regime shifts.
Disclaimer: for research and education only. Not financial advice. Trading carries risk of loss; manage your own positions. Indicator
Market Cycle Wave [Gabremoku]Market Cycle Wave is a price-based cycle indicator built to map broad market phases into a readable oscillator and a price-anchored overlay.
Instead of relying on a single signal, the script combines trend, momentum, volatility, and range-position data into a composite cycle score. That score is normalized and smoothed to create an intermediate Cycle Wave, while a slower Secular line provides broader context.
The script has two main views:
- an oscillator pane with the score histogram, Cycle Wave, Secular baseline, and major Cycle Peak / Cycle Trough labels.
- a price overlay with a cycle line, gradient aura, and a thinner secular context line.
The regime model classifies market conditions into Debt Accumulation, Deleveraging, Reflation, and Transition. The goal is not to generate standalone buy/sell signals, but to help traders read where price may sit inside a broader market cycle structure.
How to use it
This indicator works best on broad indices and diversified equity ETFs, where cycle behavior is usually cleaner than on highly erratic single names.
Typical use:
- Daily chart: monitor intermediate cycle shifts
- Weekly chart: study broader regime transitions
Practical reading:
- A rising blue cycle wave can suggest constructive expansion conditions
- A yellow rollover after a mature advance can suggest a weakening cycle structure
- Deep negative readings followed by green recovery can suggest reflation or post-stress repair
- The secular line helps show whether the shorter cycle is moving with or against the broader backdrop
The dashboard summarizes the current regime, state, direction, score, risk posture, and color legend directly on the chart.
How it works
The cycle model uses eight price-based factors:
- Fast EMA vs slow EMA relationship
- Fast EMA slope
- RSI momentum regime
- RSI extremes
- Position inside the rolling yearly range
- Distance from yearly extremes
- ATR volatility regime
- Price position vs the slow EMA
Each factor contributes to a composite score. That score is then normalized, smoothed, and accumulated over a rolling memory window to build a bounded cycle wave around a midpoint.
A second and slower baseline is built through longer smoothing to represent secular context. This creates two distinct layers:
- Cycle Wave: the intermediate cycle, more reactive to market swings
- Secular Baseline: the broader context, slower and less sensitive
Recent Cycle Peak and Cycle Trough labels are pivot-based, so the latest labels need confirmation from future bars. Indicator
Bitcoin Cycle Highs and LowsOVERVIEW
The Bitcoin Cycle Highs and Lows indicator maps out the historical macro market cycle tops and bottoms of Bitcoin, dating back to 2011. In addition to serving as a visual map of historical market phases, the indicator features an algorithmic projection engine. This engine uses various statistical and geometric decay models to forecast the date and price of future macro highs and lows based on the asset's historical behaviour.
This tool is designed for macro-level market analysis, allowing traders to visualise diminishing returns, cycle duration trends, and phase retracements.
CHART ELEMENTS
When applied to a chart, the indicator plots several visual elements:
• Vertical Cycle Markers: Solid vertical lines identify the exact date of historical macro highs (Red) and macro lows (Lime).
• Price & Date Labels: Located at the anchor of each vertical line, detailing the exact recorded date and price (formatted automatically to the chart's active currency).
• Phase Arrows (Dashed Lines): Horizontal dashed lines connecting a low to the subsequent high (Bull Phase) or a high to the subsequent low (Bear Phase).
• Phase Statistics: Floating text labels positioned at the end of each Phase Arrow. These display the duration of the phase in days, the absolute price change, and the percentage move from the previous point.
PREDICTION MODELS
The indicator includes multiple distinct mathematical models for projecting future dates and prices.
Date Predictors:
• Previous bar count: Projects the next date by applying the exact duration of the most recent corresponding cycle.
• Average: Calculates the simple arithmetic average duration of all historical cycles of the same type.
• Weighted average: Averages previous cycle lengths but applies a mathematical recency bias, giving more weight to recent cycles to account for cycle duration stabilisation.
Price Predictors:
• Previous % move: Projects the next target by applying the exact percentage multiplier of the most recent corresponding cycle.
• Average: Projects the target using the geometric mean of all historical cycle multipliers, limiting the skew of extreme outliers.
• Diminishing gains: Analyses the cycle-over-cycle rate of change. It isolates peak-to-peak or trough-to-trough macro moves, calculates the historical decay in those percentage gains, and applies the decayed growth rate to project the next target.
• Fibonacci extension decay: Evaluates swing ratios by measuring the magnitude of a phase relative to the preceding phase (for example, how far a bull market extended past the previous bear market drop). It calculates the historical decay of that extension premium and applies it to the current swing.
SETTINGS AND INPUTS
• Predictions: Determines the number of future cycle highs and lows to project (0 to 9). Set to 0 to disable projections and only view historical data.
• Date predictor: Selects the algorithmic model used to project the X-axis (time) coordinate of future cycle points.
• Price predictor: Selects the algorithmic model used to project the Y-axis (price) coordinate of future cycle points.
• Bear/Bull market arrows: Toggles the visibility of the horizontal dashed lines and their accompanying statistical labels.
• Full height backgrounds: When true, vertical cycle markers extend infinitely across the Y-axis. When false, markers anchor precisely to the price level of the previous cycle phase, creating a stair-step visualisation.
• Ignore 2011 cycle: Excludes the extreme volatility and outliers of the 2011 cycle from the indicator's mathematical averages and trend decay calculations.
• Backtest # lows/highs: A testing feature that temporarily removes the most recent 1 or 2 historical cycle points from the dataset. This allows users to test the prediction models against known outcomes to evaluate their historical accuracy.
Indicator
Daubechies D4 Denoising [LB]Concept
The Daubechies D4 Wavelet Denoising indicator applies a multi‑level discrete wavelet transform using the compactly supported Daubechies D4 wavelet (Ingrid Daubechies, 1992) combined with Donoho's universal threshold (Donoho & Johnstone, 1994). It separates price into approximation (trend) and detail (noise) coefficients, attenuates noise via soft thresholding, and reconstructs a denoised price curve that directly overlays the chart.
Mathematical Foundation
The Daubechies D4 wavelet is defined by four scaling coefficients h and four wavelet coefficients g , forming quadrature mirror filters that satisfy perfect reconstruction. At each level, the input array a is circularly convolved with h and g , then downsampled by two to produce the approximation a' and detail d' :
a' = SUM_m h * a
d' = SUM_m g * a
This process is iterated J times. The universal threshold lambda is estimated for each detail array independently using the median absolute deviation (MAD) of the coefficients :
sigma = MAD / 0.6745
lambda = sigma * sqrt(2 * log N)
Soft thresholding is then applied to each detail coefficient x :
threshold(x) = sign(x) * max(|x| - lambda, 0)
Finally, the denoised signal is reconstructed by upsampling, convolution with synthesis filters, and summation of approximation and detail contributions.
What Problem Does It Solve ?
Classical moving averages and low‑pass filters eliminate noise at the cost of significant lag and do not adapt to the local structure of the data. The Daubechies D4 wavelet denoising preserves sharp transitions (edges) while removing high‑frequency noise, offering a lag‑free, adaptive smoothing that respects the multi‑scale nature of price action.
How To Interpret
Denoised line above price – the smoothed trend is stronger than the current raw price; underlying momentum remains positive despite transient dips.
Denoised line below price – the smoothed trend is weaker; price is correcting within a larger structure.
Denoised line flattening or changing direction – a regime shift may be underway; the multi‑scale trend is losing or gaining momentum.
Parameters
Source – price field to denoise (default close).
Decomposition Levels – number of wavelet decomposition iterations. Higher levels remove lower‑frequency components, producing a smoother but more slowly reacting line.
Window Length (power of 2) – analysis window size. Must be a power of two for the dyadic decomposition; the indicator automatically adjusts to the largest valid power of two if an invalid value is entered.
Reference
Daubechies I., "Ten Lectures on Wavelets", Society for Industrial and Applied Mathematics, 1992.
Donoho D.L. & Johnstone I.M., "Ideal Spatial Adaptation by Wavelet Shrinkage", Biometrika, Vol. 81, No. 3, pp. 425‑455, 1994. Indicator
Goertzel Algorithm [LB]🔬 Concept
The Goertzel Algorithm, developed by Gerald Goertzel in 1958, is a digital signal processing technique that efficiently computes individual terms of the Discrete Fourier Transform (DFT). Unlike a full FFT which calculates all frequency bins, the Goertzel Algorithm targets a single predetermined frequency — making it the optimal tool for detecting the presence and power of a specific cycle period within a price series.
📐 Mathematical Foundation
The algorithm implements a second‑order recursive filter with a resonance at the target frequency. For a target period T , the normalized angular frequency is :
ω = 2π / T
The recurrence relation is applied to each sample x in the window :
Q = x + 2·cos(ω)·Q - Q
After processing N samples, the complex DFT coefficient is extracted without storing intermediate values :
Re = Q - Q ·cos(ω)
Im = Q ·sin(ω)
The output is the squared magnitude (power) of that frequency component :
Power = Re² + Im²
This approach requires only one multiply and two additions per sample, making it substantially lighter than a full FFT when monitoring a single cycle.
🎯 What Problem Does It Solve ?
Classic oscillators and moving averages operate blindly across all frequencies, mixing signal and noise. FFT‑based indicators attempt spectral analysis but compute hundreds of unnecessary frequency bins, wasting computational resources and introducing lag. The Goertzel Algorithm isolates the exact cycle period the trader wants to monitor, delivering pure frequency‑domain intelligence with minimal overhead.
📊 How To Interpret
Power rising and sustained at high levels → the target cycle period is strongly present in the price action ; the market is respecting the chosen rhythm.
Power declining toward zero → the target cycle has faded ; the market is no longer oscillating at that frequency.
Sharp power spike → the cycle has suddenly emerged ; potential entry signal when a known period (e.g., 20‑bar) becomes active.
Compare multiple instances with different periods → add the indicator twice with different target periods (e.g., 10 and 20 bars) to see which cycle dominates.
⚙️ Parameters
Target Period (bars) – the exact cycle length to detect ; typical values are 10, 20, 50, or any dominant cycle observed on the chart.
Analysis Window Length – number of bars over which the algorithm computes the power ; longer windows give more frequency resolution but slower response.
Source – price data used as input (close, HLC3, etc.).
📚 Reference
Goertzel G., "An Algorithm for the Evaluation of Finite Trigonometric Series", The American Mathematical Monthly, Vol. 65, No. 1, pp. 34‑35, January 1958.
Proakis J.G. & Manolakis D.G., "Digital Signal Processing : Principles, Algorithms, and Applications", Chapter 6 – Efficient Computation of the DFT, Prentice Hall, 1996. Indicator
Hilbert Bandwidth [LB]🔬 Concept
The Hilbert Bandwidth Index, derived from John Ehlers' analytic signal approach, measures the instantaneous stability of the dominant market cycle by computing the bandwidth — the absolute deviation between the raw instantaneous period and its smoothed counterpart. A narrow bandwidth indicates a clean, well-defined cycle suitable for trading.
📐 Mathematical Foundation
The price median is transformed via a 7‑coefficient FIR Hilbert Transform to extract the analytic signal's real and imaginary components :
real = 0.0962·P + 0.5769·P - 0.5769·P - 0.0962·P
imag = 0.0962·P + 0.5769·P - 0.5769·P - 0.0962·P
The instantaneous phase φ is obtained via the two‑argument arctangent of imag and real . After exponential smoothing, the phase difference Δφ between consecutive bars yields the instantaneous period :
T = 2π / |Δφ|
Finally, the bandwidth is defined as :
B = |T - EMA(T, L) |
where L is the period smoothing length. The result is expressed in bars.
🎯 What Problem Does It Solve ?
Traditional cycle indicators assume a persistent dominant cycle, producing unreliable signals during chaotic or transitional markets — the Hilbert Bandwidth quantifies cycle cleanliness in real time, allowing traders to filter out low‑quality cyclic signals and act only when the market exhibits a stable, tradeable rhythm.
📊 How To Interpret
Bandwidth below threshold (background colored) → the dominant cycle is narrow, well‑defined, and stable ; trend‑following and cycle‑based strategies have higher probability of success.
Bandwidth above threshold → the cycle is broad and unstable ; the market is either noisy or in transition ; avoid cycle‑dependent entries.
Bandwidth rapidly contracting → the market is shifting from chaos to order ; anticipate a breakout or the emergence of a clean trend.
⚙️ Parameters
Phase Smoothing – exponential smoothing length applied to the instantaneous phase (default 50) ; higher values stabilize the phase estimate but introduce lag.
Period Smoothing – EMA length applied to the instantaneous period (default 10) ; controls the responsiveness of the bandwidth calculation.
Narrow Band Threshold – the bandwidth value in bars below which the cycle is considered "clean" (default 3.0) ; the background is highlighted when bandwidth falls below this level.
📚 Reference
Ehlers J.F., "Rocket Science for Traders : Digital Signal Processing Applications", Chapter 7 – The Hilbert Transform, John Wiley & Sons, 2001.
Ehlers J.F., "Cycle Analytics for Traders", Chapter 9 – Bandwidth Measurement, John Wiley & Sons, 2014. Indicator
Bitcoin Compressing Power Law ChannelBitcoin Compressing Power Law Channel
Most Bitcoin power-law channels draw bands of a fixed width around a long-term trendline. This one is different: the channel width is not constant. It starts wide and compresses exponentially as Bitcoin matures, modeling the idea that long-term volatility around the trend tends to shrink over time. That decaying width is the core idea of this indicator.
Why a compressing channel
A standard power-law channel assumes the spread between its upper and lower bounds stays the same across Bitcoin's entire history. In practice, an asset's relative volatility tends to fall as it grows larger and more liquid. This indicator captures that by letting the channel narrow over time toward a configurable floor, so the bounds reflect a maturing market rather than a permanently fixed range.
How it works
The model assumes log(price) scales linearly with log(days since the genesis block), producing a fair-value trendline: logFair = intercept + slope * log10(days). A lower bound is offset below that line, and the upper bound is placed above the lower bound at a distance set by the channel width.
The width itself is the original part: width = minWidth + startWidth * exp(-decaySpeed * yearsSinceGenesis). Early in Bitcoin's history the exponential term is large and the channel is wide. As years pass, that term shrinks toward zero and the width converges to a minimum floor (minWidth). The result is a channel whose envelope tightens over time instead of staying fixed.
What it plots
Three lines in price space (upper, middle, lower) with a shaded fill between the upper and lower bounds. Optionally, a 200 SMA of the current timeframe and a 200 SMA from the weekly timeframe, each toggleable. The weekly SMA is requested from a higher timeframe with lookahead disabled, so it does not repaint using future data. A normalized "Decay Channel Oscillator" is exposed in the Data Window, showing where the current close sits within the channel on a 0 to 1 scale (0 = lower bound, 1 = upper bound).
Inputs
Every model parameter is adjustable: the genesis date, the power-law intercept and slope, the lower offset, the initial and minimum channel widths, and the decay speed that controls how fast the channel compresses. Colors for each line, the fill, and both SMAs are configurable.
How to use it
Apply it to a Bitcoin chart on a longer timeframe such as Daily or Weekly, where a power-law model is most meaningful. The middle line is the model's central estimate; the upper and lower lines describe the expected long-term range, narrowing as time goes on. The Data Window oscillator lets you read how stretched price is within the channel numerically.
Parameters and calibration
The default intercept and slope are starting values that approximate Bitcoin's historical power-law fit. They are not fixed truths. You should re-evaluate them and adjust them, along with the offset, widths, and decay speed, to suit your own analysis and the data range you are studying. Different calibrations will move the channel and change how aggressively it compresses.
Limitations and cautions
This is a model, not a prediction. The power-law relationship is an empirical observation that may break down at any time, and the decay parameters are assumptions, not facts. The compressing width is a hypothesis about volatility maturing over time; it may not hold. This indicator is built for Bitcoin and is not intended for other assets. Nothing here forecasts future prices, and the past behavior of the channel does not guarantee anything about how price will behave going forward.
The code is open-source under the Mozilla Public License 2.0. You are welcome to study it and build on it. Indicator
Long-Term Cycle Valuation MapLong-Term Cycle Valuation Map is an educational indicator designed to visualize long-term crypto market valuation and cycle conditions.
The script does not generate buy or sell signals. It does not predict exact tops or bottoms. Its purpose is to help users observe whether the market is in a deeper reset, rebuild, neutral, late expansion, or exhaustion-risk environment.
The indicator combines several long-term market-regime components into one normalized Cycle Valuation Score.
The model uses:
1. 365D Moving Average Multiple
This measures price relative to its 365-day moving average. It helps visualize whether price is extended above or depressed below a long-term mean.
2. RSI(100) on 2D
This measures slower momentum conditions using a long RSI setting on a 2-day timeframe.
3. Long-Term Bollinger Bandwidth
This measures long-term volatility compression and expansion using a 365-day Bollinger Bandwidth structure.
4. Market Attention Proxy
This is not Google Trends data.
It is a market-based activity proxy using volume, volatility, and range expansion. Its purpose is to estimate whether market activity is quiet, normal, elevated, or overheated from price and volume behavior.
Customization:
Each component can be turned on or off.
Users can also adjust the relative strength of each component through percentage inputs.
The default public configuration is:
365D Moving Average Multiple: 30%
RSI(100) on 2D: 30%
Long-Term Bollinger Bandwidth: 30%
Market Attention Proxy: 10%
The weights do not need to add up to exactly 100. The script automatically normalizes the active components.
If a component is disabled, or if it does not have enough historical data yet, it is excluded from the active score.
The table shows how many components are active.
The final output is a normalized Cycle Valuation Score between 0 and 100.
General interpretation:
Below 15:
Deep reset zone
15-90:
Broad cycle range. This can include rebuild, neutral, and late expansion conditions.
Above 90:
Exhaustion-risk zone
The score should not be used as a standalone trading system.
A low score does not mean price must immediately rise.
A high score does not mean price must immediately fall.
Markets can remain in the same regime for extended periods.
The script is intended for higher-timeframe market-structure analysis. It is best used on multi-day, weekly, and monthly charts.
On early historical bars, the score may use fewer available components until all long-term calculations have enough history. The table shows how many components are active.
This indicator combines common long-term market measures into a single normalized framework. Its usefulness comes from organizing valuation, momentum, volatility, and market-activity conditions into one cycle-regime score.
Repainting:
The script does not use future data or lookahead logic.
Values on the currently open candle may update until that candle closes.
Limitations:
The script does not forecast future prices.
It does not guarantee cycle tops or bottoms.
It does not provide trade entries or exits.
It should not be used as a standalone trading decision tool.
Intended use:
Educational long-term market-structure and cycle-valuation analysis. Indicator
DAILY OPEN LEVELS NCO X MALL THE MALL X NCO SYSTEM
**MALL X NCO** is a proprietary, custom-built trading framework designed to map institutional-grade price geometry onto your charts. Developed from scratch, this system automates session-open mechanics by combining volatility-based expansion zones with a strict mathematical price grid.
Here is how the two creator-designed engines work together:
### 1. The MALL Engine (Proprietary Volatility Expansion)
* **What it does:** It tracks real-time market expansion starting exactly at the session open.
* **How it helps you:** Instead of using lagging indicators, it calculates precision mathematical bands (\pm 1\text{SD}, \pm 2\text{SD}, \pm 3\text{SD}) based on the asset's active momentum.
* **The Goal:** It immediately highlights extreme overbought or oversold zones, marking the exact boundaries where the market is stretching too far.
### 2. The NCO Engine (Mathematical Price Grid)
* **What it does:** It instantly projects a fixed, percentage-based or point-based grid across the chart at the start of the session.
* **How it helps you:** It slices price action into clean, highly visible technical levels (e.g., +0.5\%, +1.0\%, -0.5\%).
* **The Goal:** It removes all guesswork by providing fixed, unemotional targets for Take Profit (TP) and Stop Loss (SL) based on clean numbers.
### 🎨 The Creator's "Elite Matrix" Interface
Built specifically to eliminate mental fatigue and emotional trading under heavy risk, the visual interface uses a highly intentional, clean design:
* **Pure White:** The absolute Session Open price—the unbreakable 0% benchmark.
* **Steel Gray Zones:** Normal market noise (\pm 1\text{SD}). The "hands-off" area to protect your capital.
* **Emerald Green & Neon Red:** High-contrast execution lines for snajper entries, profit-taking, or invalidation cuts.
### 🚀 Built For High-Risk Precision
* **Candle Close Native:** Designed specifically to align with **Candle Close Validation** rules—preventing fakeouts and live-bar trap chasing.
* **Real-Time HUD Dashboard:** A custom on-screen table tracking your exact distance from the open price and predicting the next algorithmic key levels.
* **Instant Alerts:** Automated alerts trigger the exact second a candle closes or tests any core MALL or NCO boundary.
> **The Blueprint:** Designed by traders, for traders. No retail fluff, no useless clutter—just pure, cold mathematical geometry.
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Indicator
Meme Season Score | Memecoin Cycle Timing
One number, 0 to 100, that answers a single question: is it meme season right now?
The Meme Season Score is a composite oscillator that condenses six different memecoin-cycle factors into one decision-relevant signal. Instead of staring at half a dozen separate dominance and market-cap charts trying to interpret what the data is saying together, you get a single weighted reading and a climate label.
▸ WHY THIS INDICATOR EXISTS
Existing memecoin tools on PulseWire each do one narrow thing: one plots a meme dominance ratio, one shows Z-scores of individual coins, one is an EMA crossover on a single sector index. None of them blend multiple cycle factors into a single comparable score.
Generic "altseason indices" treat all alts as a homogeneous block — they cannot tell you whether memecoins specifically are leading or lagging the broader alt rotation. Memecoins behave differently from L1s, DeFi, or RWAs. They need their own framework.
This script is that framework: six factors, all relevant to memecoin cycle behavior, all weighted by their historical importance, all blended into one number you can act on.
▸ METHODOLOGY
Each of the six input factors is first converted to a rate-of-change over a rolling momentum window (default: 14 bars). That ROC is then converted to a percentile rank within a longer normalization window (default: 180 bars), giving a 0–100 score that reflects "where does today's reading sit within the recent distribution."
Inverse factors (where falling values are bullish for memes) have their percentile rank flipped before contributing to the composite.
The six factors and default weights:
• MEME.D trend — 25% — meme sector dominance rising = bullish
• MEME.C momentum — 20% — meme sector market cap accelerating = bullish
• BTC.D inverse — 20% — BTC dominance falling = capital rotating to alts
• OTHERS.D trend — 15% — altcoin dominance rising = risk-on environment
• STABLE.C inverse — 10% — stablecoin cap declining = stables being deployed
• MEME.C/TOTAL acceleration — 10% — meme share growing faster than market
All weights are user-adjustable in the inputs and are auto-normalized, so they don't have to sum to 100.
Note: MEME.D is not currently a native CRYPTOCAP ticker on PulseWire, so it is derived as MEME.C / TOTAL × 100 inside the script.
▸ CLIMATE ZONES
The score is divided into five regimes, each with its own color and emoji label that appears on the chart:
• 0–20 ❄️ Meme Winter Capital fleeing memes (deep accumulation zone)
• 20–40 🌧️ Cool Mixed signals — selective plays only
• 40–60 ☀️ Warming Up Rotation beginning — early meme season
• 60–80 🔥 Meme Season Active Broad memecoin pumps — high conviction window
• 80–100 🚀 Peak Mania Extreme readings — historically precedes retracements
The main score line shifts color as it crosses zone boundaries. Background of the pane tints faintly with the current zone color (toggleable). A label on the last bar shows the live score and zone name.
▸ HOW TO READ IT
• Score above its 50-period EMA = momentum is strengthening
• Score below its 50-period EMA = momentum is weakening
• Cross above 60 = season conditions activating
• Cross above 80 = extreme conditions, historical risk zone
• Cross below 40 = season cooling off
• Cross below 20 = winter conditions, sentiment capitulation
The 50-EMA line is the slower trend reference; the colored line is the live signal. Watching their relationship is often more useful than watching either one alone.
▸ HOW TO USE IT
The script pulls all of its data from CRYPTOCAP indices via request.security, so the chart symbol does not affect the calculation. Putting it on CRYPTOCAP:MEME.C on the Daily timeframe gives the cleanest visual context (price chart of the meme sector above, score sub-pane below) but you can use any chart.
The default calculation timeframe is Daily, which is appropriate for cycle-level analysis. The score will show the same Daily-derived value regardless of what chart timeframe you are viewing.
▸ INPUT SETTINGS
Calculation Settings:
• Calculation Timeframe (default: Daily)
• Momentum Lookback in bars (default: 14)
• Normalization Lookback in bars (default: 180)
• Score Smoothing EMA (default: 3 — set to 1 for raw unsmoothed score)
Factor Weights — all six factor weights are individually adjustable from 0 to 100. Weights are auto-normalized so any combination is valid.
Display Options:
• Toggle the 50-period EMA of the score
• Toggle the floating score label
• Toggle the background climate tint
• Label size (small / normal / large / huge — use huge for screenshots)
▸ BUILT-IN ALERTS
Four alert conditions are defined and can be activated through the standard Add Alert dialog:
• 🔥 Meme Season Starting (score crosses above 60)
• 🚀 Peak Mania Warning (score crosses above 80)
• ☁️ Meme Season Ending (score crosses below 40)
• ❄️ Meme Winter (score crosses below 20)
▸ LIMITATIONS AND HONEST CAVEATS
• This is a contextual/regime tool, not a predictive one. The score tells you the current state of the meme cycle based on factors that have historically mattered. It does not predict future prices or guarantee any outcome.
• Percentile rank is by definition backward-looking. The score reflects how today's momentum compares to the recent past, not where prices are going.
• With default settings, the script needs roughly 194 daily bars of valid CRYPTOCAP data to warm up before producing a meaningful score (14-bar ROC plus 180-bar percentile window). MEME.C history begins in early 2024, so this is not a constraint for current charts.
• Memecoin market structure changes quickly. Tokens that drove the sector last cycle may be irrelevant in the next. The score works at the sector level and is robust to individual token churn, but it cannot tell you which specific memecoin to buy.
• Factor weights are calibrated to behavior observed in available CRYPTOCAP history. If the underlying market structure shifts substantially, weights may need adjustment.
▸ TECHNICAL NOTES
• Pine Script v6
• Open-source under the Mozilla Public License 2.0
• Uses 5 request.security calls (well below the 40-call limit), all to official CRYPTOCAP indices
• No repainting — all calculations use confirmed bar close values from the requested timeframe
▸ DISCLAIMER
For educational and informational purposes only. This script is a market analysis tool, not financial advice. Nothing here constitutes a recommendation to buy or sell any asset. Past behavior of the score in historical data is not a guarantee of future behavior. Cryptocurrency markets, and memecoin markets in particular, are highly volatile and can result in substantial losses. Always do your own research and trade with risk you can afford to lose.
Indicator
Volatility Regime Cycle [AGPro Series]Volatility Regime Cycle
🌀 Overview
Volatility Regime Cycle classifies every bar on your chart into one of four distinct volatility phases: Contraction, Expansion, Climax, and Reset. Unlike traditional trend or regime indicators that focus on price direction, this tool maps the cyclical behavior of volatility itself — helping traders recognize whether the market is coiling, releasing, climaxing, or resetting. Each phase is detected through a multi-factor confluence engine and displayed with gradient background shading, transition markers, and S/R-style climax reaction zones. The framework is asset- and timeframe-agnostic: it adapts to crypto, forex, indices, stocks, and commodities on any timeframe.
💎 Unique Edge
Most volatility tools present a single metric (ATR, Bollinger Width, VIX proxy). Volatility Regime Cycle differs in structure and intent:
🔸 Phase-based classification, not just a reading — every bar is assigned to a named regime with a trader-actionable bias.
🔸 Multi-factor confluence scoring — five independent volatility inputs (ATR level, BB Width level, BB/KC squeeze, volume z-score, ATR rate-of-change) vote on the active phase. No single factor can dominate.
🔸 Winsorized normalization — outlier events (single extreme bars) do not compress the scale and hide current readings, a common flaw in simple percentile-based tools.
🔸 Climax Reaction Zones — each Climax event is preserved as an S/R-style rectangle with mid-pivot line, creating a memory of past volatility exhaustion levels that often act as future reaction areas.
🔸 Cycle-aware analytics — tracks historical phase durations and estimates current cycle progress based on rolling averages of past phases of the same type.
🔸 Phase-specific Trader Bias — panel translates the current regime into a plain-language bias (Breakout-watch, Momentum-favor, Reversal-risk, Cooldown).
This is not a Wyckoff phase tool, an Elliott counter, or a Dow-theory classifier. It is a pure volatility-cycle mapper, engineered from the ground up to stand apart from both classical cycle indicators and single-metric volatility meters.
🧠 Methodology
The engine runs three layers:
🔹 Factor Layer
• ATR Level — 14-period ATR, winsorized min-max normalized (5%-95% range) over a configurable lookback window.
• BB Width Level — Bollinger Band width as percent of basis, normalized identically.
• Squeeze State — true when Bollinger Bands are contained inside Keltner Channels (classic volatility compression).
• Volume Z-Score — standardized volume relative to its rolling mean and standard deviation.
• ATR Rate-of-Change — momentum of volatility itself.
🔹 Scoring Layer
Each of the four phases has its own scoring formula that weights the five factors differently. For each bar, all four phase scores are calculated in parallel, and the phase with the highest score is the candidate regime for that bar.
🔹 Confirmation Layer
To suppress whipsaw, the candidate phase must persist for a configurable number of bars (default 3) before replacing the active phase. A minimum phase duration lock additionally prevents rapid flips. Climax events include a de-duplication cooldown so that clustered climax bars produce a single marker rather than a cluster of overlapping labels.
Phase transitions are classified as major (Contraction→Expansion breakouts and Climax entries) or minor (all other routine changes). Only major transitions receive labels; minor changes are shown as subtle dotted lines to keep the chart clean.
🔔 Signals & Alerts
The script exposes alerts for every phase transition as well as two high-value composite events:
🔸 Any Phase Transition — fires whenever the active phase changes.
🔸 Entered Contraction / Expansion / Climax / Reset — fires for specific phase entries.
🔸 Contraction → Expansion (Breakout) — coil release event; of interest to breakout traders.
🔸 Climax Entry (Exhaustion Warning) — volatility peak event; of interest to mean-reversion and risk-management traders.
All alerts fire only on confirmed bar close to prevent intra-bar flip-flop.
⚙️ Key Inputs
🔹 Engine Settings — normalization lookback, ATR length, Bollinger/Keltner length and multipliers, volume z-score length, ATR rate-of-change length, confirmation bars, minimum phase duration.
🔹 Phase Thresholds — low volatility level, high volatility level, climax volatility gate, climax volume z-score threshold, climax de-dup cooldown.
🔹 Visuals — toggles for background shading, major transition labels, minor transition lines, volatility ribbon, current phase label.
🔹 S/R Zones — climax zones toggle, breakout zones toggle, maximum active zones, zone initial length, zone range lookback.
🔹 Panel — show/hide, location, Dark/Light theme, font size.
🔹 Label Sizing — font size for on-chart labels.
🔹 Alerts — per-event toggles.
📘 How to Use
🔸 Breakout traders: watch for Contraction phase on the panel with Trader Bias showing Breakout-watch. When the phase transitions to Expansion, a coil release is underway and a Breakout label is printed. Optional Breakout Zones can be enabled to preserve the breakout level as a retest reference.
🔸 Momentum / trend traders: ride the Expansion phase while Trader Bias reads Momentum-favor. Phase Duration and Cycle Progress on the panel give a sense of where the current momentum leg sits relative to historical averages.
🔸 Mean-reversion / exhaustion traders: a Climax label with Trader Bias Reversal-risk highlights volatility exhaustion. The Climax Reaction Zone drawn at each climax often behaves as a future reaction level and can be used as confluence with other reversal tools.
🔸 Risk managers: the Reset phase with Trader Bias Cooldown typically signals reduced market conviction and can be used to scale down position size until a new Contraction builds up.
🔸 Multi-timeframe reading: run the script on the higher timeframe for regime context and on the lower timeframe for entry timing.
Hover the panel header to see a statistics tooltip with average durations of each phase over the last completed cycles.
⚠️ Limitations & Transparency
🔹 The script does not predict future prices or issue buy/sell recommendations. It is a classification and context tool.
🔹 Phase detection is inherently lagging because it requires the confirmation window and minimum duration lock. This is a deliberate design choice to suppress whipsaw at the cost of some responsiveness.
🔹 Normalization uses a rolling lookback window; the first lookback bars after loading the script may show compressed or unstable readings while the window fills.
🔹 Cycle Progress is an estimate based on historical phase averages and may exceed 100% when the current phase runs longer than past cycles.
🔹 Climax and Reset scores rely partly on volume; on instruments with unreliable or missing volume feeds, volume-dependent factors will contribute less.
🔹 All visual elements are cosmetic and toggleable; they do not alter the underlying phase logic.
🛡️ Risk Disclosure
This indicator is a technical analysis tool. It is not a trading system, not a signal service, not financial advice, and not a guarantee of future results. Trading involves substantial risk of loss. Past market behavior does not predict future market behavior. Users are solely responsible for their own trading decisions, risk management, and position sizing. Always test any tool on your preferred instruments and timeframes with appropriate historical review before using it as part of a live decision-making process. Indicator
BTC Valuation Cycle [Alpha Extract]A sophisticated multi-metric Bitcoin valuation framework that synthesizes on-chain analytics including SOPR, MVRV, Price-to-Realized, and Mayer Multiple into a unified 0-100 cycle oscillator with six-tier zone classification for market cycle identification. Utilizing logistic transformation with configurable weighting and z-score normalization, this indicator delivers institutional-grade Bitcoin-specific valuation assessment with pivot-based extreme detection and comprehensive alert system. The system's weighted composite architecture combined with adaptive curve intensity enables precise calibration of cycle sensitivity while maintaining statistical validity across Bitcoin's multi-year market cycles.
🔶 Advanced Multi-Metric Synthesis Engine
Implements sophisticated composite calculation combining four distinct Bitcoin valuation metrics with configurable weighting and normalization framework. The system retrieves SOPR (Spent Output Profit Ratio), MVRV (Market Value to Realized Value), Price-to-Realized ratio, and Mayer Multiple from on-chain sources, applies z-score normalization to each metric over configurable periods, transforms via logistic function for 0-100 scaling, and generates weighted average creating unified cycle score.
// Component Score Calculation
SOPR_Centered = SOPR - 1.0
SOPR_Z = z_score(SOPR_Centered, Normalization_Length)
SOPR_Score = logistic_100(SOPR_Z, Curve_Intensity)
Price_to_Realized_Z = z_score(Price / Realized_Price, Normalization_Length)
PR_Score = logistic_100(Price_to_Realized_Z, Curve_Intensity)
MVRV_Z = z_score(Market_Cap / Realized_Cap, Normalization_Length)
MVRV_Score = logistic_100(MVRV_Z, Curve_Intensity)
Mayer_Z = z_score(Mayer_Multiple, Normalization_Length)
Mayer_Score = logistic_100(Mayer_Z, Curve_Intensity)
// Weighted Composite
Cycle = (SOPR_Score × W_SOPR + PR_Score × W_PR + MVRV_Score × W_MVRV + Mayer_Score × W_Mayer) / (W_SOPR + W_PR + W_MVRV + W_Mayer)
🔶 Understanding Bitcoin Valuation Metrics
SOPR (Spent Output Profit Ratio) measures the degree of profit for coins moved on-chain, calculated as value sold divided by value paid. Values above 1.0 indicate profitable selling (distribution), below 1.0 indicate loss-taking (capitulation). The system centers SOPR around 1.0 for normalization.
MVRV (Market Value to Realized Value) compares current market cap to realized cap (aggregate cost basis). High MVRV signals overvaluation as price exceeds average acquisition cost; low
MVRV suggests undervaluation. The system offers Ratio mode (raw MVRV), Z-Score mode (statistical deviation), or Blend mode (average of both).
Price-to-Realized Ratio directly compares current BTC price to realized price (realized cap divided by circulating supply), providing cleaner valuation signal than MVRV by removing market cap distortions.
Mayer Multiple measures price relative to 200-day moving average. Values above 2.4 historically mark tops; values near or below 1.0 mark bottoms. The system normalizes this classic technical indicator alongside on-chain metrics.
🔶 Logistic Transformation Framework
Features sophisticated logistic function application converting unbounded z-scores into bounded 0-100 range with configurable curve intensity controlling sensitivity. The system applies formula: 100 / (1 + exp(-z × k)) where z is z-score and k is curve intensity (default 0.90), creates S-curve transformation preserving relative relationships while preventing extreme outliers, and enables smooth gradient visualization across entire cycle range.
🔶 Six-Tier Cycle Zone Classification
Implements comprehensive market cycle framework dividing 0-100 range into six distinct zones with configurable thresholds representing Bitcoin's characteristic bubble and bust patterns. The system defines Bottom Extreme (default <10, accumulation zone), Cold Zone (10-25, early recovery), Lower Mid (25-40, neutral to bullish), Upper Mid (40-60, bullish), Hot Zone (60-75, late bull market), and Top Extreme (>75, euphoria/distribution) with dynamic color coding.
🔶 Pivot-Based Extreme Detection System
Provides intelligent local extreme identification using pivot high/low detection with zone threshold filtering and visual capsule markers. The system detects pivot highs above Hot Zone threshold and pivot lows below Cold Zone threshold using configurable left/right bars, creates horizontal capsule visualizations at exact extreme values with color-coded centers (red for tops, cyan for bottoms), and maintains rolling array limited to maximum capsule count for clean chart presentation.
🔶 MVRV Calculation Mode Selection
Offers three distinct MVRV calculation approaches optimizing for different market conditions and analytical preferences. Ratio mode uses raw Market Cap / Realized Cap for direct valuation comparison, Z-Score mode applies statistical normalization emphasizing deviations from historical mean, and Blend mode (default) averages both approaches balancing absolute valuation with statistical context for robust signal generation.
🔶 Configurable Metric Weighting System
Features flexible weight allocation enabling traders to emphasize preferred metrics or disable unreliable components during specific market regimes. The system accepts 0.0-N weight values for each metric (default 1.0 all equal), automatically handles missing data by excluding NA metrics from composite, recalculates weighted average dynamically, and enables custom cycle calibration based on trader's confidence in different on-chain signals.
🔶 Confirmed HTF Data Integration
Implements rigorous anti-repaint methodology using confirmed higher-timeframe values with offset preventing live bar distortion. The system retrieves all on-chain metrics from daily timeframe with 1-bar offset ensuring only completed daily candle data influences cycle score, applies identical offset to Mayer Multiple calculation, and maintains signal stability across real-time updates preventing false extreme alerts.
🔶 Comprehensive Alert Framework
Provides five distinct alert conditions covering critical cycle events and threshold breaches with descriptive messages. The system triggers Top Extreme alert on crossover above top threshold (default 90), Bottom Extreme alert on crossunder below bottom threshold (default 10), Hot Rejection alert when cycle falls from Hot Zone, Cold Reclaim alert when cycle rises from Cold Zone, and Mayer Threshold breach alert for traditional technical confirmation.
🔶 Gradient Zone Visualization Architecture
Creates intuitive color-coded area plot with six distinct color zones reflecting current cycle position through visual spectrum from cyan (extreme bottom) through purple/orange to red (extreme top). The system applies dynamic zone coloring to both area fill and cycle value display, implements configurable area transparency (default opaque), and maintains consistent color scheme across oscillator pane, table values, and capsule markers.
🔶 Real-Time Diagnostics System
Features comprehensive data availability monitoring with missing metric labels and detailed value table showing all component metrics. The system detects NA values in SOPR, Realized Price, MVRV, or Mayer Multiple, displays warning label listing unavailable metrics, and provides table overlay showing current values for Cycle score, all four components, MVRV-Z, Mayer MA, and threshold with color-coded formatting.
🔶 Performance Optimization Framework
Employs efficient calculation methods with null-safe division functions, optimized array management for capsule storage, and conditional plotting minimizing unnecessary rendering. The system includes streamlined weighted average calculation skipping NA metrics, smart capsule cleanup maintaining maximum limit through oldest-first deletion, and minimal recalculation overhead through var declarations and confirmed bar logic.
This indicator delivers sophisticated Bitcoin-specific valuation analysis through multi-metric on-chain synthesis unavailable in traditional technical indicators. By combining SOPR (profit/loss behavior), MVRV (cost basis valuation), Price-to-Realized (pure valuation), and Mayer Multiple (technical context) into unified cycle framework with statistical normalization, it provides comprehensive market cycle assessment grounded in blockchain fundamentals. The six-tier zone system maps directly to Bitcoin's characteristic 4-year halving cycles with Bottom Extreme zones historically marking generational buying opportunities and Top Extreme zones marking distribution phases. Perfect for long-term Bitcoin investors seeking data-driven cycle timing, position sizing based on valuation extremes (increase allocation in Cold/Bottom zones, reduce in Hot/Top zones), and objective framework for navigating Bitcoin's volatile multi-year cycles with alerts providing advance warning of major cycle transitions requiring portfolio reassessment. Indicator
BTC Potential EnergyBTC Potential Energy is a macro-cycle oscillator that tracks how much "dry powder" is sitting in Tether (USDT) relative to its structural baseline — and translates that into a 0–100 potential energy score for Bitcoin. The core idea is simple: when investors are parking abnormal amounts of capital in stablecoins, that capital isn't gone — it's coiled. The higher the stablecoin accumulation above its own historical trend, the greater the potential for a violent rotation back into Bitcoin when sentiment shifts.
The indicator displays as a sub-pane oscillator beneath your BTC chart and is designed primarily for use on the Weekly or Daily timeframe , where macro cycle analysis is most meaningful.
The Concept: Stablecoins as a Coiled Spring
In crypto markets, Tether Dominance (USDT.D) is the percentage of total crypto market cap held in USDT. It rises when investors flee risk — selling Bitcoin and altcoins into stablecoins — and falls when investors deploy that capital back into the market.
This creates a physics-like analogy:
Compression phase — USDT.D rises as capital moves to safety. Like compressing a spring, potential energy builds.
Release phase — USDT.D begins to fall. The spring releases. Capital rotates into BTC, historically preceding or coinciding with the early stages of bull runs.
The further above normal USDT.D is, and the more abruptly it starts declining, the more powerful that rotation tends to be.
The Problem With Naive USDT.D Analysis
The most obvious approach — ranking the raw USDT.D value over history — fails in practice. Why? Because the stablecoin market has grown enormously since 2017. USDT.D in 2021 was structurally higher in absolute percentage terms than in 2018, simply because more stablecoins exist and are used as a base layer across DeFi and centralised exchanges. This secular uptrend means that if you rank raw USDT.D, the indicator reads "high energy" throughout the 2021 bull market — precisely when energy was already deployed and Bitcoin was already running. That is the opposite of useful.
The Solution: Detrended Potential Energy
BTC Potential Energy solves this by ranking the deviation of USDT.D from its own long-term moving average , not the raw level itself. This strips out the structural growth of the stablecoin market and isolates only the anomalous accumulation — the excess fear-driven or cycle-driven flight to safety that goes beyond what the baseline trend would predict.
Step 1 — Establish the Baseline
A long Simple Moving Average (default: 100 bars) is computed on USDT.D. On the weekly chart, this represents approximately 2 years — roughly one full Bitcoin market cycle. This MA acts as the "expected" or structural level of stablecoin dominance for any given period. It rises gradually over time as the stablecoin ecosystem matures, automatically adjusting the baseline to the era.
Step 2 — Compute the Deviation
The deviation is calculated as:
Deviation = USDT.D − Baseline MA
A positive deviation means USDT.D is elevated above its own trend — investors are accumulating stablecoins beyond what the baseline predicts. This is abnormal stablecoin hoarding, and it represents genuine potential energy.
A negative deviation means USDT.D is below trend — capital has already been deployed into risk assets. Energy has been discharged.
Step 3 — Percentile Rank the Deviation
The current deviation is ranked as a percentile against all deviation values in a rolling lookback window (default: 200 bars). This produces the final Potential Energy score on a 0–100 scale:
100 = The current stablecoin accumulation anomaly is the most extreme it has been in the entire lookback window. Maximum coiled energy.
50 = Deviation is average. Neutral state.
0 = USDT.D is at its most suppressed relative to trend. Capital is fully deployed. Energy is discharged.
This approach is robust across all market eras and does not require re-calibration as the stablecoin ecosystem grows.
The Four Energy States
The indicator identifies one of four states on every bar, displayed in the live info table and used to determine histogram colour.
ACCUMULATING (Blue)
PE is below 40. USDT.D is near or below its structural baseline. Capital is deployed or neutral. The market is in an active risk-on phase or the bear market has not yet produced meaningful stablecoin accumulation. No elevated potential energy.
BUILDING (Amber)
PE is between 40 and the Charge Threshold, and is rising. Stablecoin accumulation is growing above the baseline. Investors are beginning to retreat from risk. Potential energy is loading. Worth monitoring but not yet at an actionable level.
CHARGED (Orange/Red)
PE is above the Charge Threshold (default: 65). USDT.D is historically elevated relative to its own trend. A significant amount of capital is sitting in stablecoins beyond what the baseline predicts. The spring is fully coiled. Bitcoin's potential energy is at its most loaded.
RELEASING (Green)
PE is above the Charge Threshold AND USDT.D deviation has been declining for N consecutive bars (default: 3). This is the critical state — energy that was compressed is now actively unwinding. Capital is rotating out of stablecoins. Historically, this condition — high stablecoin accumulation followed by a structural reversal — has preceded or coincided with meaningful Bitcoin bull moves.
Release Signal Logic
The release signal is intentionally conservative. Two conditions must be met simultaneously:
1. Armed: The Potential Energy score must be at or above the Charge Threshold. The spring must actually be compressed before a "release" means anything. A declining USDT.D from a low base is not a release — it's just noise.
2. Declining: USDT.D deviation must have been falling for at least N consecutive bars (configurable). This filters out single-bar blips and requires a structural turn, not just a one-week dip.
When both conditions are met, the histogram turns green for the duration of the release phase, and an alert can be triggered on the first bar the signal fires.
Visual Guide
Histogram colour
Deep Blue → Sky Blue: Low energy (PE 0–50), capital deployed
Gold: Moderate energy (PE 50–threshold), building phase
Amber/Orange: High energy (PE above threshold), fully charged
Green: Release phase active — deviation unwinding from a high base
Background glow: Subtly tints the pane background to reflect the current energy state — deep blue at low energy, warming to amber and orange as energy builds.
Dashed orange line: The Charge Threshold. PE crossing above this line arms the release detector.
Dotted grey line: The 50 midpoint. PE above 50 means the deviation is in the upper half of its historical range.
Fast MA (blue) / Slow MA (pink): Moving averages of the USDT.D deviation, projected into the 0–100 PE space. When fast crosses above slow, deviation is accelerating upward — energy building faster. When fast crosses below slow from above the threshold, it can precede a release signal.
Info Table (top right):
Energy Level — Current PE score out of 100
USDT.D — Raw live Tether Dominance reading
Baseline — The long MA value, the structural floor
Deviation — How many percentage points USDT.D is above or below baseline (+ is elevated, − is deployed)
State — Current energy state in plain text
Trend MA — The baseline length setting in use
Settings Reference
Percentile Lookback (default: 200)
The rolling window used to rank the current deviation. Longer lookbacks give more historical context but are slower to respond to structural shifts. 200 bars on the weekly is approximately 4 years — long enough to capture a full bull/bear cycle.
Trend Baseline MA (default: 100)
The most important parameter. This defines the structural floor. On the weekly chart, 100 bars is roughly 2 years — approximately one Bitcoin market cycle. Shorter values (e.g. 52 bars = 1 year) make the baseline more responsive, which can be useful on the daily chart. Longer values (130–150 bars) create a smoother, slower-moving baseline that irons out mid-cycle noise.
Signal Smoothing (default: 3)
EMA applied to raw USDT.D before any calculations. Reduces candle-to-candle noise in the source data. Higher values produce a cleaner but more lagged signal.
Charge Threshold (default: 65)
The PE level that must be reached before the release detector is armed. Raising this to 70–80 produces fewer, higher-conviction signals. Lowering it to 55–60 will trigger signals more frequently but with potentially lower reliability.
Consecutive Bars Declining (default: 3)
The number of consecutive bars that the deviation must be falling before a release is confirmed. Increasing this requires a more sustained reversal and reduces false positives. On the weekly chart, 3 bars is already meaningful — that is 3 weeks of sustained stablecoin outflows.
Fast MA / Slow MA Length (defaults: 14 / 50)
Moving averages of the deviation plotted in PE space. The crossover of fast above slow while PE is below threshold is worth watching as early warning of building energy. A crossover of fast below slow from above the threshold can precede a release signal.
Recommended Usage
Timeframe: Weekly or Daily. This is a macro cycle indicator. Do not use it to time intraday entries — it is not designed for that.
Combine with price structure: The release signal is most powerful when it aligns with Bitcoin reclaiming a key level, a breakout of a multi-month range, or a bullish divergence on a momentum indicator. The Potential Energy score tells you the setup is primed — price action confirmation tells you it is firing.
Watch the Deviation column: The live table shows the raw deviation in percentage points. A deviation of +1.5% means USDT.D is 1.5 percentage points above its 2-year average — that is a meaningful anomaly. Watching this number decline from a peak as the state transitions from CHARGED to RELEASING gives an intuitive real-time read of the rotation.
Baseline MA tuning: On the weekly chart, start with the default 100. On the daily chart, consider reducing the Trend Baseline MA to around 52 bars to keep the baseline responsive to faster-moving daily USDT.D data.
Alerts
Three alert conditions are available:
BTC PE — Energy Release: Fires on the first bar the release condition is met. The most actionable alert. USDT.D deviation is actively unwinding from an elevated zone.
BTC PE — Fully Charged: Fires when PE crosses above the Charge Threshold from below. Signals that potential energy has entered the high zone.
BTC PE — Energy Exiting High Zone: Fires when PE crosses below the Charge Threshold from above. Useful as a heads-up that the setup may be resolving.
Notes
This indicator uses request.security("CRYPTOCAP:USDT.D") to pull Tether Dominance data sourced from CoinMarketCap's crypto market cap feed via PulseWire.
This indicator is a research and analysis tool. It does not constitute financial advice. Past correlations between Tether Dominance behaviour and Bitcoin price movements do not guarantee future results. Always combine macro oscillator readings with your own price analysis, risk management framework, and market context. Indicator
