Volume Footprint, Absorption & Imbalance Analysis by GurujamesHere is a breakdown of exactly what the tool does and how it helps you analyze the market.
1. Intrabar Order Flow Splitting (Delta Calculation)
Instead of just showing total volume, the script peers into the 1-minute timeframe inside your current candle to calculate the Volume Delta.
What it does: It separates aggressive market buying from aggressive market selling.
Why it matters: It tells you who is actually in control. A candle might close green, but if the delta is heavily negative, it means sellers were aggressively hitting the bid, but buyers held the line.
2. Trapped Trader Detection (Absorption Bubbles)
The script identifies exact moments when aggressive traders get trapped by passive limit orders from larger participants.
What it does: When extreme selling pressure fails to push the price down (leaving a bullish wick), or extreme buying pressure fails to push the price up (leaving a bearish wick), it triggers an absorption event.
Visual Output: It plots a circular bubble above or below the wick. Inside the bubble is the exact percentage of that candle's total volume that was absorbed.
Example: A green bubble reading "72%" means 72% of the bar's volume was aggressive selling that completely failed to move the market down.
3. Institutional Imbalance Zones (Extending Boxes)
This feature finds areas where the market became extremely one-sided, leaving a "vacuum" in the order book.
What it does: It scans for high-volume candles where one side outpaced the other by 300% or more (a 3:1 ratio).
Visual Output: It draws a semi-transparent, extending box (Green for Buy Imbalances, Red for Sell Imbalances) originating from the extreme of the candle.
Why it matters: These areas act as high-probability Supply and Demand zones. Because the move was so aggressive, liquidity was skipped. The market will very often retrace back to these boxes to "mitigate" or fill the skipped orders. The boxes auto-delete after an hour (configurable) to keep your chart clean once they become stale.
4. Unfinished Liquidity Magnets (Missed Auctions / Poor Extremes)
In auction market theory, a healthy market sweeps the high or low until volume tapers off to zero. When it doesn't, it creates a "poor" high or low.
What it does: It detects candles that close at their absolute highest or lowest tick while both buyers and sellers are still actively transacting high volume.
Visual Output: It highlights the upper or lower body of that specific candle with a bright extending box (Green for Missed Buys, Red for Missed Sells), accompanied by a small cross ().X
Why it matters: These zones represent "unfinished business." The market is highly likely to revisit these exact levels later to properly sweep the liquidity that was left hanging. You can toggle these visual zones on or off in the settings.
5. Real-Time Analytics Dashboards
The script paints two distinct data tables on your chart to give you micro and macro perspectives without having to do any math yourself.
The Macro Table (Top Right): Keeps a rolling 7-day memory of market aggressiveness. It shows you the total percentage of volume over the last week that resulted in trapped buyers vs. trapped sellers, helping you gauge the broader structural trend.
The Micro Table (Bottom Right): Acts as a live ticker for the active, moving candlestick. It updates tick-by-tick to show you the current bar's absorption percentages, whether an imbalance has triggered, and explicitly states the structural status (e.g., "BULLISH (Absorbing Sells)" or "Neutral"). אינדיקטור
GMS Session Rays (Sydney/Asia/London/NY)A lightweight Pine v6 indicator that plots the previous completed session’s High and Low for the four major sessions—Sydney, Asia, London, New York—so you always see the most actionable structure levels without chart clutter. Lines auto-update at the end of each session and extend right as horizontal rays. Labels are clean, stack automatically to avoid overlap, and can be placed on the left or right side of the chart.
What it shows
Previous session High/Low for each enabled session (not the current live session).
Right-extended rays at those prices, updated when the session closes.
Optional labels per session (e.g., “sydney high”, “london low”), with auto-stacking to prevent overlaps.
Customization
Per-session toggles: show/hide each session; show/hide labels per session.
Style controls: color, width, and line style (Solid/Dotted/Dashed) per session.
Label controls: global on/off, Left/Right placement, bars offset, Y-offset (in ticks), size (Tiny/Small/Normal), auto-stacking with adjustable step.
Session windows: editable HHMM-HHMM for Sydney/Asia/London/NY.
Timezone: set a single indicator timezone (default America/New_York).
Only Today mode: clears older rays daily to keep charts minimal.
How it works (under the hood)
Tracks High/Low only while a session is active; when it ends, those values are frozen and plotted as the previous session levels. אינדיקטור
IV Probability Ranges - SuiteIV Probability Ranges
IV Probability Ranges is a volatility-based range and market-behavior study. It uses the selected implied-volatility index to build a projected range around the opening price of each day, week, month, quarter, half-year, or year.
The script divides that range into configurable levels and tracks how price historically behaved around them.
Main features:
Implied-volatility range centered on the period open
Support for VIX, VXN, RVX, VXD, GVZ, OVX, VXFXI, VXEEM, VXTYN, and VXEW
Daily through annual range periods
Configurable divisions inside the main range
Additional standard-deviation and extension levels
Historical reach rates for each upper and lower level
Reversion-versus-continuation statistics after a level is reached
First-touch statistics showing whether the upper or lower side was reached first
Box breach, return-to-open, and close-back-inside statistics
Optional prior-period VWAP and VWAP deviation references
Adjustable rolling sample size
How the statistics work:
“Reach” shows how often price touched a level during completed historical periods.
After a level is reached, the script also records whether price moved back to the nearest inner level or continued to the nearest outer level first.
The optional first-touch section compares matching upper and lower levels and records whether the upside, downside, or neither side was reached first.
All statistics are calculated from completed periods using the available chart history and selected sample size.
How to use it
Choose a period and the volatility index most relevant to the chart symbol. Adjust the range divisions, extension levels, and sample size as needed.
The tool can be used to:
Compare the current move with the implied range
Identify historically common or uncommon price extensions
Study whether price tended to revert or continue after reaching a level
Compare upside and downside first-touch behavior
Add volatility context to another trading method
Limitations:
This script is a research and context tool, not a trading system.
Historical results depend on the selected symbol, timeframe, volatility index, settings, chart history, and sample size. Implied volatility does not guarantee that price will remain inside a range or reach a specific level.
Historical bars also do not always reveal the exact intrabar order of events, so some same-bar situations require a consistent tie-breaking assumption.
VWAP features require usable volume data.
Originality
The script combines implied-volatility ranges, historical level-reach statistics, reversion-versus-continuation tracking, first-touch analysis, breach statistics, and prior-period VWAP references into one configurable study.
The Pine implementation and combined feature set were developed for this publication. The underlying concepts of implied volatility, standard deviations, and VWAP are established market concepts.
Version note
This script replaces an older publication with a similar title, but it is not a minor revision or repackaged version of that script.
The underlying modeling engine was substantially redesigned and expanded. The new version uses a different statistical framework and adds rolling historical samples, level-specific reach analysis, conditional reversion-versus-continuation tracking, first-touch race statistics, extended range modeling, breach and return analysis, and period-matched VWAP references.
Because the new script functions differently from the prior model, and because TradingView’s Update feature does not allow the publication title to be changed, it was released as a separate script. The older publication was marked as deprecated so users would not continue relying on the obsolete version.
Future revisions to this model will be published through the Update feature. אינדיקטור
BTC Correlation - short clubBTC Correlation % — Indicator Description
Author: Short Club / @DemianNagoga
Version: Pine Script v6
Type: Indicator (non-overlay, separate pane)
Overview
The BTC Correlation % indicator measures how closely an altcoin's price movements follow Bitcoin in real time. It uses Pearson correlation on 1-bar rate-of-change (RoC) values over a configurable lookback window, giving you a clear signal of whether the altcoin is riding BTC's coattails or moving independently.
How It Works
RoC Calculation — Computes the 1-bar % change for both the current chart symbol and BTC.
Pearson Correlation — Runs ta.correlation() over the user-defined lookback (default 50 bars).
Percentage Scale — Multiplies the correlation coefficient by 100, yielding a range from −100% to +100%.
Color-Coded Columns — The histogram is split into four segments, each plotted as a separate column-style plot for clean color separation.
Color Zones & Interpretation
Zone Range Meaning
🟢 Green > 70% High correlation — altcoin closely follows BTC
🟡 Yellow 30–70% Moderate correlation — partial BTC influence
⚪ Gray 0–30% Weak correlation / decoupling — altcoin lives its own life
🔴 Red < 0% Inverse correlation — altcoin moves opposite to BTC
A dashed zero line sits at 0% for visual reference.
On-Chart Table
A small overlay table (position configurable: top-right, top-left, bottom-right, bottom-left) displays:
Ticker — current chart symbol
BTC Corr. — current correlation value in % (color-coded by zone)
Rating — qualitative label: Strong (>70%), Moderate (30–70%), Weak (0–30%), Inverse (<0%)
Input Parameters
Parameter Default Description
BTC Symbol BINANCE:BTCUSDT.P BTC pair used as benchmark
Correlation Lookback 50 Number of bars for Pearson correlation
Show Table true Toggle the on-chart info table
Show Correlation Line true Toggle the histogram columns
Table Position top_right Placement of the info table
Use Cases
Altcoin scalping — Know instantly whether your alt is following BTC or running on its own catalyst.
Decoupling detection — Gray zone = potential breakout candidate independent of BTC direction.
Hedging signals — Red zone (inverse) = altcoin moving opposite to BTC; useful for pairs or hedging.
Swing context — Avoid fading BTC trend on a highly-correlated alt; size down when correlation drops.
Credits
Built for the Short Club community. If you reuse or build upon this script, please credit @DemianNagoga. אינדיקטור
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. אינדיקטור
Event Probability Engine [Quantum Algo]Event Probability Engine
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🔶 OVERVIEW
Event Probability Engine is a statistical probability indicator that answers one question at the close of every bar: based on the measurable conditions active right now, what is the historical probability that price closes higher one, three, and five days from today? Instead of subjective pattern reading, the script builds and maintains a live rolling database of forward returns conditioned on eighteen observable market events — day-of-week seasonality, oversold and overbought readings, volume spikes, streaks, range position, volatility regime, pivot touches, and an optional lunar control — then pools the currently active events into a single composite probability, displayed as a TODAY headline, a full per-event statistics table, and a shaded forecast cone projected on the chart.
It is designed for the daily timeframe. On other timeframes, the one, three, and five day horizons become one, three, and five bars.
🔶 WHAT IS AN EVENT STUDY?
An event study measures what a market historically did after a defined, observable condition occurred — for example, what happened over the next five days every time the Relative Strength Index closed oversold, or every Monday, or every time volume spiked two standard deviations above normal. This indicator runs eighteen such studies continuously, in real time, on the chart's own data, and keeps every study honest with the statistical safeguards described below.
🔶 WHY THIS SCRIPT IS ORIGINAL
1. A live event database in Pine. Each of the eighteen events maintains its own rolling, capped sample of forward returns at three horizons, tagged with the market regime at the moment the event fired — a self-updating event-study framework, not a fixed backtest.
2. Shrinkage estimation. Every win rate is pulled toward fifty percent by a configurable number of pseudo-samples. An event with fifteen samples cannot display an extreme probability, because fifteen samples cannot justify one.
3. Overlap correction. State-based events (for example, an oversold reading persisting for a week) generate autocorrelated, overlapping samples that inflate apparent sample size. The effective sample size is deflated by the horizon length before any confidence calculation.
4. Wilson score bounds. Next to each five-day win rate, the table shows the Wilson confidence lower bound computed on the corrected sample size — the number an event must clear before its edge deserves trust, not its raw point estimate.
5. Regime conditioning with fallback. When enough samples exist in the current regime (bull or bear, defined by the two-hundred period exponential moving average), statistics are computed on regime-matched samples only, marked ® in the table. A bear-market Thursday is not assumed to behave like a bull-market Thursday.
6. Quality-weighted log-odds pooling. Active events are combined by weighted log-odds — a method related to Bayesian evidence combination — rather than naive win-rate averaging, so one strong, well-sampled edge is not diluted by three weak ones.
7. A built-in falsification control. Lunar phase events are included deliberately so the engine can audit a popular claim empirically: if full and new moons carry no edge, their quality scores sit near zero and they contribute nothing to the composite. A probability framework should be able to demonstrate which inputs fail, not only which appear to work.
🔶 HOW IT WORKS
Event detection: On every bar close the script evaluates all eighteen conditions — Monday through Friday, adaptive or fixed oversold and overbought thresholds, volume z-score spikes, up and down streaks, range-low and range-high position, volatility expansion and compression by percentile rank, confirmed pivot support and resistance touches within an Average True Range distance, and the optional lunar events.
Database recording: Whenever an event was active one, three, or five bars ago, the realized forward return is stored in that event's arrays, first-in-first-out at a configurable cap, together with the regime tag from the moment the event fired.
Per-event statistics: The table reports, for every event, the shrinkage-adjusted win rate at each horizon, the Wilson lower bound, sample count, average forward return, profit factor, a zero-to-one-hundred quality score blending edge magnitude, sample sufficiency, and recent consistency, and the resulting directional bias.
Composite probability: Active events passing the minimum-sample filter are pooled by quality-weighted log-odds into the TODAY headline (next-day probability of an up close with a visual meter), the one, three, and five day composite row with expected returns and a strength grade, and a projected forecast path with a shaded plus-and-minus one standard deviation cone drawn from the current close.
Chart layer: Optional regime background tint, the regime line, live pivot support and resistance rails with prices, and historical event markers on the candles so past occurrences of every event can be reviewed directly on the chart.
🔶 HOW TO USE IT
1. Apply it to a daily chart of any liquid symbol — cryptocurrency, stocks, indices, forex, gold, futures. Let it load its history; sample counts grow with available bars.
2. Read the TODAY headline first: the next-day probability, the meter, and the expected one-day return.
3. Scan the table for the highlighted rows — those events are active right now. Judge each by its Wilson lower bound and quality score, not the raw win rate.
4. Use the composite row and forecast cone as context: STRONG requires both a meaningful probability distance from fifty percent and high average quality.
5. Treat readings near fifty percent as exactly what they are: weak evidence. This engine is intentionally built to display small honest numbers rather than large misleading ones.
6. Combine with your own analysis — the engine measures conditional history; it does not know tomorrow's news.
🔶 SETTINGS
- Database: sample cap per event, minimum samples for composite inclusion, minimum regime-matched samples, shrinkage strength.
- Events: oscillator length and thresholds (fixed or adaptive percentile), volume z-score, streak length, range lookback, pivot lookback and touch distance, lunar events on or off.
- Statistics: Wilson z-score (default 1.645, a ninety percent one-sided bound).
- Display: dashboard position and five text sizes, forecast cone, regime tint, regime line, pivot rails, candle markers.
🔶 ALERTS
- Composite Bias Change — fires once per bar close whenever the five-day composite bias flips state, with the current one-day and five-day probabilities in the message.
🔶 FREQUENTLY ASKED QUESTIONS
Does the indicator repaint? Statistics are recorded and evaluated on closed bars, and pivot events use confirmed pivots with their standard confirmation lag. The dashboard and forecast update on the live bar by design, as a dashboard should.
Why do most probabilities sit near fifty percent? Because genuine conditional edges in daily data are small, and the shrinkage and overlap corrections are built to say so. Extreme displayed probabilities on thin samples are the signature of a dishonest tool.
What does the ® mark mean? That event currently has enough regime-matched samples, so its statistics are computed only from the current bull or bear regime rather than the full history.
Why are moon phases in a statistics tool? As a falsification control. The engine should be able to show which inputs carry no edge — and the user can watch it do exactly that.
Can I use it intraday? Yes, but the horizons become bars instead of days, and day-of-week events lose their meaning. The design intent is the daily timeframe.
🔶 CREDITS
This script stands on standard, publicly documented statistical methods, gratefully credited: the Wilson score interval by Edwin B. Wilson (1927), Laplace-style shrinkage estimation, and the event-study methodology long established in quantitative finance. Their combination into a live, regime-conditional, overlap-corrected event database with quality-weighted log-odds composite pooling, implemented entirely in Pine Script with capped arrays and user-defined types, is original work — no third-party or open-source script code was reused.
🔶 LIMITATIONS
Probabilities derived from historical conditioning are estimates, not guarantees, and conditional edges in daily data are typically small. Sample databases need history to mature; young charts produce thin, heavily shrunk statistics by design. Day-of-week events assume a five-day session calendar. Regime conditioning depends on the two-hundred period regime definition. This is a research and confluence tool, not a standalone trading system.
🔶 DISCLAIMER
This script is provided strictly for educational and informational purposes. It is not financial advice, an investment recommendation, or a solicitation to buy or sell any financial instrument. Past statistical behavior does not assure future results. Trading involves substantial risk. Always do your own research and manage risk independently. אינדיקטור
ATR Divided by 4he Average True Range (ATR) is the gold standard for measuring market volatility. However, for active intraday traders, scalpers, or those looking to fine-tune their risk management, the standard ATR can often feel too wide.
Enter the Fractional ATR (ATR / 4). This indicator calculates the traditional Average True Range and divides it by four, isolating exactly 25% of the asset’s recent average volatility.
Why Divide ATR by 4?
Using a fraction of the ATR allows traders to adapt to market noise on a more granular level. Here is how you can apply the ATR/4 to your trading strategy:
High-Probability Intraday Targets: If an asset typically moves $4 a day (Standard ATR), aiming for a $1 move (ATR/4) represents a highly realistic, high-probability profit target for day traders and scalpers.
Tighter, Volatility-Adjusted Stop Losses: Using a full 1x or 2x ATR for a stop loss can sometimes mean risking too much capital or giving back too much floating profit. Using ATR/4 allows you to trail your stops tightly while still factoring in the asset's current micro-volatility, keeping you out of the standard "market noise."
Grid Trading and Scaling In: If you build positions over time, using an arbitrary static number (like buying every $0.50 down) ignores market conditions. Spacing your limit orders by an ATR/4 distance ensures your grid adapts to expanding or contracting volatility.
How it Works
The math is straightforward and transparent:
It calculates the standard Average True Range based on your chosen period.
It divides that exact value by 4.
It plots the resulting value as an easy-to-read oscillator in a separate pane below your chart.
Features & Settings
Customizable ATR Length: By default, the indicator uses the industry-standard 14-period lookback. You can easily adjust this in the settings menu to fit your specific timeframe or strategy (e.g., a 5-period for hyper-responsive data, or a 21-period for smoother data).
Clean Visuals: Plots cleanly in a lower pane so it does not clutter your main price chart.
Best Timeframes
This indicator is universally applicable but shines particularly well on lower timeframes (1m, 5m, 15m) when trying to capture a fraction of the Higher Timeframe (1H, 4H, Daily) volatility.
Disclaimer: This script is for educational and analytical purposes only. Always backtest your risk management strategies before applying them to live capital. אינדיקטור
Sessions+ (M1D)Sessions+ maps the ICT trading day as liquidity. It tracks the Asia, London and New York session highs and lows, frames the midnight (00:00) opening range, and reads your daily bias, premium/discount, resting liquidity and average range on one dashboard — everything you'd otherwise mark up by hand, kept current automatically.
Session levels (Asia / London / NY)
Each session's high and low are drawn from the exact candle that formed the extreme (not the session's start/end time) and projected forward as a liquidity level:
A session high is buy-side liquidity (resting stops above price). A session low is sell-side liquidity (resting stops below price).
A level stays live — bold colour, extending line — until price trades back through it. The moment that happens the level is "swept"/"mitigated": the line freezes in place and dims, so tapped liquidity fades into the background instead of cluttering the chart, but stays visible for context.
Every level carries a dated label (e.g. ASIA.H 06/07) so you always know which day a level belongs to, even several days back.
Session Days Back (0–5) — how many prior days of session levels stay on the chart in addition to today. 0 = today only (default); set to 2 to see the last 3 days of Asia/London/NY levels, each still fading correctly when tapped.
Core session windows plus optional carry windows (Asia carries to 02:00, London to 09:30, NY to 16:00) — the level keeps tracking new extremes through this follow-on period, not just the core window, since price often makes its real high/low after the "session" clock ends.
12am Opening Range
The first 30 minutes of the ICT trading day (00:00–00:30 NY) — the day's first pool of liquidity:
Boxes the 00:00–00:30 range and draws its high and low from the exact wick that made them (labelled 12am.H / 12am.L), plus a centred 12am tag on the box marking the open.
Each level holds until a candle body closes fully through it (not just a wick tap — a confirmed close), or until 05:00 NY (London Kill Zone close) if nothing has taken it by then. Either way, the level then freezes and dims like a session level.
Its own Trading Days Back (0–5), separate from the session setting above, so you can keep a different history depth for the 12am range vs. the sessions.
Dashboard — what every row means
The panel (top-right by default) is a live readout, refreshed every bar:
— BIAS —
Daily Dir: Bullish or Bearish — simply whether price is currently trading above or below today's 00:00 (midnight) open.
Bias: the actual trade bias, based on how far price sits into the prior dealing range (see Premium/Discount below) — not just which side of a line it's on:
Bullish — price is in discount (bought down into the lower half of the range) and below the midnight open — both signals agree.
Lean Bullish — price is in discount, but still trading above the midnight open (signals disagree, weaker read).
Bearish / Lean Bearish — the mirror image, price in premium.
Neutral — price is genuinely camped around the 50% equilibrium (inside the adjustable Bias Neutral Band %), i.e. no real edge either way. Bias never reports a vague "mixed" result — it always commits to a lean unless price is truly balanced.
— PREMIUM / DISCOUNT —
PDH / PWH / PMH and PDL / PWL / PML — the high and low of the dealing range you select in settings: Previous Day, Previous Week, or Previous Month. This is the range ICT traders use to judge premium vs. discount.
Each shows a ✓ (green) if that level is still open/unswept, or a ✗ (red) once price has traded through it this period.
EQ 50% — the exact midpoint of that dealing range (the equilibrium), plus a live read: premium (above EQ — expensive, favour selling), discount (below EQ — cheap, favour buying), or above PDH / below PDL if price has broken outside the range entirely.
— LIQUIDITY (today) —
Asia H / Asia L, London H / London L, NY H / NY L — today's session levels, each with the same ✓ open (green) / ✗ swept (red) marker as above, so you can tell at a glance which pools of liquidity are still resting and which have already been run.
— 12am OPENING RANGE —
12am Open — the exact 00:00 NY opening price, with its live distance from current price.
12am Rng — the size (in points) of the 00:00–00:30 opening range.
12am OR H / 12am OR L — the range's high/low, again with ✓/✗ sweep status.
— ADR (N-Day) — ("ADR" = Average Daily Range — the typical size, in points, of a full trading day over your chosen lookback)
ADR — the average range figure itself, plus % used — how much of that typical daily move has already printed today (e.g. "112% used" means today has already moved further than an average day, which flags a potentially exhausted/extended move).
Proj Hi / Proj Lo — simple range projections: today's low + ADR (a possible high target), and today's high − ADR (a possible low target) — a rough gauge of how much room is statistically "left" in the day.
Day Rng — today's actual realised range so far, for comparison against the ADR figure.
Settings
Sessions — timezone, core + carry windows per session, Session Days Back, line width, mitigated-dim %, session label size.
12am Opening Range — show/hide, range window, Trading Days Back, active window (the 05:00 cutoff), box fill and level line colours/width, label colour.
Dashboard — show/hide, screen position, text size, which Dealing Range to use for premium/discount (Day/Week/Month), ADR lookback length, Bias Neutral Band %, and the bullish/bearish/neutral/open/swept colours.
ICT logic in one line
London and New York run the liquidity that Asia and the prior period left resting; the midnight open is the true day open and the pivot for premium/discount; the 12am range is the very first pool the new day creates. This tool keeps all four of those — sessions, midnight range, dealing-range bias, and average range — in front of you at once.
Notes
Best on intraday timeframes (30 minutes or lower recommended for the 12am Opening Range; the session levels work across any intraday timeframe).
Session-based (not a fixed UTC offset), so everything tracks correctly through daylight-saving changes.
A level's date stamps when it opened, not the trading day it belongs to — e.g. Asia opens at 6pm NY, so its label shows the prior calendar date, which is when that range actually printed.
Daily/weekly/monthly and ADR data are pulled anti-repaint (confirmed prior-period values only); every swept/taken state is confirmed on candle close, never mid-bar.
Built by M1D. For education and the study of price delivery — not financial advice.
(New and improved version of the previous "Sessions Highs And Lows Unmitigated" script.) אינדיקטור
QSX Crypto Regime Heatmap - AI Pattern Match | 10 CoinsQSX Crypto Regime Heatmap scores the trend health of 10 crypto assets on a
continuous 0-100 scale and renders them as a color-coded dashboard — so you
can read the health of the whole market in a single glance, without flipping
through 10 charts.
This is a market-overview dashboard, not a trading system. It answers one
question fast: which coins are in a strong regime right now, and which are
breaking down.
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WHAT IT SHOWS
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For each of the 10 assets, the table displays:
• Price — live price, auto-formatted for large caps and micro-caps
• 24h — daily change with ↑/↓ direction and green/red coloring
• Score — trend health, 0 (weakest) to 100 (strongest)
• Regime — a visual strength bar, red → yellow → green
• Match — AI Pattern Match confidence (explained below)
A Top 3 Strongest / Weakest panel sits at the bottom for an instant read on
where relative strength is concentrated.
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HOW THE SCORE WORKS
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The 0-100 Trend Health score blends three continuous signals — not simple
binary above/below-MA flags:
1. Distance from the 200-period MA (how far price is extended)
2. Slope of the 200-period MA (how strong the underlying trend is)
3. Directional bias (which side of the MA price sits on)
A volatility-health component then rewards stable, orderly trends and
discounts high-volatility chop, using a rolling ATR percentile.
ADAPTIVE SCORING automatically adjusts the weight between trend and
volatility per coin, based on how persistent that coin's trend has been —
so trending assets and choppy assets are judged on their own terms.
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AI PATTERN MATCH
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The "Match" column uses a K-Nearest-Neighbors model. It builds a feature
vector from the current regime (trend, volatility, MA slope) and searches
each coin's own history for the most similar past setups, then reads what
happened next.
• High — historically similar regimes tended to resolve upward
• Mid — mixed / neutral historical outcome
• Low — historically similar regimes tended to resolve downward
• Wait — not enough history yet to form a reliable match
Pattern Match is a context signal, not a prediction. Treat it as "what has
this regime tended to lead to," never as a guarantee.
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CUSTOMIZE YOUR WATCHLIST
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4 fixed blue-chips (BTC, ETH, SOL, BNB) anchor the board.
6 fully customizable slots let you drop in any symbols you want — majors,
alts, or your current rotation. No waiting for an update to track a new coin.
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ALERTS
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• Strong Breakout — any tracked coin crosses ABOVE score 70
• Weak Breakdown — any tracked coin crosses BELOW score 30
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HOW TO USE
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★ Best used on the 4H or 1D timeframe. This is a regime dashboard — its job
is to read the bigger picture, and higher timeframes give cleaner, more
stable scores.
★ On very low timeframes (1m–15m) the panel needs to pull deep history for
10 assets and will load noticeably slower. That is expected. If you want
a fast, stable board, stay on 4H / 1D.
★ Green cluster = broad strength, favor long-biased setups on your own
system. Red cluster = broad weakness, tighten risk.
★ Use the Top 3 panel to spot where relative strength is rotating.
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NOTES & LIMITATIONS
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• In broad bear phases, most scores will sit low together — that is a correct
reflection of the market, not a malfunction.
• The panel updates on the latest bar. Historical bars intentionally do not
render the table.
• Symbols default to BINANCE pairs; you can swap any slot to another exchange.
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DISCLAIMER
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This indicator is for educational and informational purposes only. It is not
financial advice, not a recommendation to buy or sell any asset, and not a
trading system. Scores, Pattern Match values, and alerts describe historical
and current market conditions — they do not predict future prices. Crypto
markets are highly volatile and you can lose money. Always do your own
research and manage your own risk. Past behavior of similar regimes does not
guarantee future results. אינדיקטור
אינדיקטור
אינדיקטור
Bitcoin 4-Year Cycle Map【說明欄位 (Description)】
Bitcoin has experienced more than a decade of market cycles, each characterized by explosive expansions, deep corrections, and prolonged accumulation phases. While every cycle has unfolded under different macro conditions, their overall timing has remained remarkably consistent.
This indicator does not attempt to predict price. Instead, it aims to answer a more important question: Is Bitcoin still following its historical four-year cycle?
► Historical Cycle Structure
The script marks Bitcoin’s major historical cycle tops and bottoms, then projects the next theoretical cycle windows by extending the historical timing (approx. 1428 days) between previous turning points.
• Cycle Tops: 2013-11-25 / 2017-12-11 / 2021-11-08 / Projected: 2025-10-06
• Cycle Bottoms: 2015-01-12 / 2018-12-15 / 2022-11-21 / Projected: 2026-10-05
► Time, Not Price
The projected labels represent time windows, not price targets. Markets can arrive early, arrive late, or ignore historical timing altogether. The objective is not to forecast price, but to observe whether Bitcoin continues to respect its long-term cyclical rhythm.
► Cycle Backgrounds
Background shading highlights the broader market environment:
• Red zones: Historical bear-market periods between cycle tops and bottoms.
• Green zones: Accumulation, recovery, and expansion phases leading into the next cycle peak.
► Why This Matters & Best Used With
Spot ETFs, institutional capital, and global liquidity have the potential to reshape Bitcoin’s historical cycle. Having an objective time framework helps you recognize when the future begins to look different from the past.
This is a macro timing framework, not a trading signal. Best viewed on Weekly/Monthly charts and combined with market structure, trend analysis, and macro liquidity.
► UI Translation & Settings
The indicator includes a language toggle in the settings. Non-Chinese speakers can select "English" from the input menu to switch all chart labels (Cycle Top / Cycle Low).
• 語言 / Language: Switch between 中文 (Chinese) and English.
• 顯示牛/熊市背景區域: Show bull/bear background zones.
• 顯示週期標籤: Show cycle labels.
• 顯示未來預測點: Show future projected points.
⸻⸻⸻⸻⸻⸻⸻⸻
【繁體中文說明】
比特幣四年週期地圖
► 概述
比特幣經歷了十多年的市場循環，每一輪都伴隨著快速擴張、劇烈修正，以及漫長的累積階段。雖然每一次循環都有不同的背景，但時間節奏卻始終展現出驚人的相似性。這個指標並不是用來預測價格，而是試圖回答一個更重要的問題：比特幣，是否仍然遵循四年週期？
► 歷史週期結構
本指標標示了比特幣歷史上最具代表性的週期高點與週期低點，並依照過去週期的時間間隔（1428天），延伸出下一個理論性的時間窗口。
• 週期高點：2013-11-25 / 2017-12-11 / 2021-11-08 / 未來預測：2025-10-06
• 週期低點：2015-01-12 / 2018-12-15 / 2022-11-21 / 未來預測：2026-10-05
► 預測的是時間，而不是價格
未來標籤代表的是時間窗口，而不是價格目標。市場可以提前、延後，甚至完全偏離歷史節奏。本指標關注的是市場是否仍然維持相似的時間結構，而非預測下一個價格高點。
► 週期背景
為了讓週期更加直觀，本指標加入了背景區域：
🟥 熊市區間：從歷史週期高點延續至週期低點。
🟩 牛市／復甦區間：從歷史週期低點延續至下一輪高點。
► 為什麼值得關注？
ETF、機構資金、全球流動性等因素都可能改變比特幣的週期。我們更需要一套客觀的時間框架，去觀察市場究竟是在延續歷史，還是開始進入新的階段。
► 建議搭配分析
本指標並非交易訊號工具。最佳使用時間框架為 Weekly 與 Monthly。建議搭配市場結構、趨勢分析、鏈上數據與宏觀流動性一起使用。歷史從不保證重演，但它經常留下值得研究的節奏。真正值得觀察的，不是市場是否完全重複過去，而是它從什麼時候開始，不再重複過去。
💡 小提醒：
這次發布時，請務必記得將你的 K 線圖切換到 Weekly (週線) 或 Monthly (月線)，然後把畫面拉遠，讓這幾個週期的標籤和背景顏色漂亮地呈現出來，再按下 Publish 發布。這樣的圖表乾淨又有說服力，絕對能順利過審！ אינדיקטור
אינדיקטור
אינדיקטור
SEDAT XI Crypto AI BIAS ENGINE-iphone v2.0 ** ⚡SEDAT XI Crypto AI BIAS ENGINE⚡
The **SEDAT XI Crypto AI BIAS ENGINE** is a multi-asset cryptocurrency dashboard designed to help traders quickly identify where momentum, trend, and participation are aligning across the market.
Rather than focusing on a single chart, the dashboard continuously scans major cryptocurrencies and summarizes the information into an easy-to-read institutional-style interface. It combines trend analysis, breakout detection, momentum, volume activity, and RSI into one compact view, making it easier to prioritize the strongest opportunities.
### Features
• Multi-asset crypto scanner (BTC, ETH, SOL, ADA, XRP, SHIB)
• AI-style bias engine with Bullish, Bearish, Strong Trend, and Breakout detection
• Institutional volume activity meter
• Momentum score with color-coded strength
• RSI momentum confirmation
• Live current price display
• Final trade bias summary
• Mobile-friendly dashboard mode
• Adjustable dashboard size and screen placement
The goal is simple: reduce chart clutter and provide a fast market overview so traders can spend less time searching and more time focusing on high-quality setups.
This indicator is designed for educational and informational purposes. It does not predict future price movements or guarantee profitable trades. Always combine its signals with sound risk management and your own market analysis.
Thank you for checking out **SΞDAT XI Crypto AI BIAS ENGINE**. I hope it becomes a valuable part of your trading workflow. Feedback and constructive suggestions are always welcome as the project continues to evolve.
אינדיקטור
NICS Yesterday Box PRONICS Yesterday Box PRO automatically plots the previous trading day's High, Low, and Midpoint, providing clean institutional reference levels for intraday trading.
Designed for Smart Money Concepts (SMC), ICT, price action, futures, forex, crypto, indices, and commodities.
Features
• Automatic Yesterday High (YH)
• Automatic Yesterday Low (YL)
• Automatic Yesterday Mid (50%)
• Auto-refresh at the beginning of every trading day
• Optional line extension
• Customizable colors and line width
• Lightweight and optimized Pine Script v6 implementation
Best Used For
• Intraday support & resistance
• Liquidity targets
• Market structure analysis
• Breakout confirmation
• Mean reversion setups
• ICT / SMC trading models
• Session-based trading
Markets
Works on all TradingView-supported markets:
• Forex
• Cryptocurrency
• Stocks
• Futures
• Commodities
• Indices
Recommended Timeframes
Optimized for:
• 1 Minute
• 3 Minute
• 5 Minute
• 15 Minute
• 30 Minute
• 1 Hour
About NICS
NICS (Neural Intelligent Cognitive System) develops professional AI-powered trading tools and institutional market analysis solutions for discretionary and systematic traders.
© AI Byte Consult Ltd.
NICS AI Ecosystem אינדיקטור
Macro Thesis Fleet: Direction & Cause OverlayMacro Thesis Fleet Overlay
A read-only macro context panel for your chart. Instead of a single trend arrow, it shows how a fleet of independent macro theses currently lean on a mapped symbol — plus the top causal claim behind that lean.
What it shows (top-right table)
Asset name — human label for the matched symbol
Direction — LONG, SHORT, or MIXED from fleet vote aggregation
Room % — estimated unpriced move remaining (Tight / Moderate / Significant band)
Strength label — e.g. Clear signal, Mixed fleet, Flagged (when thesis quality gates fail)
Fleet lean — count of theses leaning up / down / neutral (when available)
Cause one-liner — the dominant D1-level macro claim driving the read (not a price summary)
How direction is computed
Each mapped symbol carries a pre-computed direction code from upstream thesis aggregation:
LONG — net tradable lean is bullish after quality filters
SHORT — net tradable lean is bearish after quality filters
MIXED — material disagreement across the thesis fleet (no forced one-sided arrow)
This is macro context, not an intraday entry signal. Use it as a filter before your own timeframe and risk rules.
How symbol matching works
On the last bar, the script builds candidate keys from syminfo.tickerid, exchange:ticker, and bare ticker, then looks up the first match in parallel embedded arrays (MACRO_TV_KEYS, MACRO_SYMBOLS). If no match, the panel states that the chart symbol is not in the current feed.
Data cadence (important)
Values are embedded at publish time as Pine string/int/float arrays — Pine cannot call external APIs on Community scripts. Republish this script when you need a refreshed snapshot. The embedded Generated: comment in source shows the bake timestamp.
Mapped symbols in this release (31)
BTC · XAUUSD · XAGUSD · NVDA · MSFT · META · GOOGL · AMZN · SPY · QQQ · IWM · GLD · GC · XLE · GDX · TLT · EURUSD · USDJPY · EURJPY · PA · KIE · FXY · AEM · RGLD · URA · UST · NUGT · VALE · TECK · XLRE · VNQ
Matching examples: BINANCE:BTCUSDT, OANDA:XAUUSD, NASDAQ:NVDA, AMEX:SPY.
How to use
Add to a chart for one of the mapped symbols above.
Read direction + room + cause in the panel.
If direction is MIXED or strength is Flagged, treat the read as low conviction until you verify contributing theses yourself.
Republish when the embedded snapshot is stale for your workflow.
Not financial advice. Macro snapshot only — not a trading system. אינדיקטור
Hurst Cycles What it is . An implementation of J.M. Hurst's nominal cyclic model. Hurst's premise: price movement is partly the sum of several nested cycles of roughly fixed wavelength (20-day, 40-day, 80-day, 20-week, 40-week, 18-month, 54-month...), harmonically related — each roughly half the length of the next — plus an underlying trend and noise. The indicator detects each cycle's troughs from price pivots, marks troughs and peaks with stacked diamonds (peaks defined properly, as the highest high between consecutive troughs), draws each cycle as a sine wave phased to its last trough, sums the enabled cycles into a composite model line that rides the candles, projects expected future trough dates as vertical lines with a tolerance window, and offers FLDs (price displaced forward half a wavelength — crossings generate Hurst's classic targets). Wavelengths are defined in calendar days on the daily timeframe and auto-rescale so the same cycle structure appears on any chart timeframe.
How to use it properly. The workflow that matches how Hurst actually worked: start on the daily chart with everything at defaults and check whether the diamonds are landing near obvious lows — if the instrument's real cycles run consistently longer or shorter than nominal, adjust the wavelength inputs until troughs line up (Hurst expected the nominal values to be starting points, not universal constants). Then trade the synchrony: the meaningful moments are when several cycles trough together — the composite dipping while multiple vertical windows cluster in the same zone is the signal Hurst's whole method builds toward, and one cycle's window alone is weak evidence. Use the manual anchors as your judgment layer: pivot confirmation takes half a wavelength, so when you believe a major low just printed, enter its date and price and the model re-phases immediately — that's how you keep the projection current instead of half a cycle stale. And treat the tolerance windows as zones to watch for a turn with confirmation from price, never as dates to blindly buy.
Downfalls — read these before trusting it with money. The structural ones first: cycle troughs confirm half a wavelength after they occur, so every automatic phasing is backward-looking by design — the 18-month cycle's trough isn't machine-confirmed until ~9 months later (manual anchors are the workaround, but then the phasing is your opinion). Second, the tolerance window is a heuristic, not Hurst's statistics — real Hurst analysis derives timing variance from the instrument itself, and this ±% is a stand-in you should tune. Third, the model is phase-only: amplitude weighting is a wavelength-based approximation, and the composite says nothing about how far price moves, only roughly when it might turn. Fourth, pivot detection is mechanical — it will happily phase a cycle off a news-spike low that a human analyst would skip, and in strong trends the shorter cycles' troughs get dragged late (Hurst's own observation). Practical ones: future projections extrapolate calendar time from recent bar spacing, so on stock charts distant dates drift slightly since future weekends aren't skipped; the biggest cycles can't pivot-confirm on intraday charts (Pine's 5000-bar lookback limit) and rely on manual anchors there; history only draws as far back as bars loaded on your chart; and each new confirmed trough re-phases everything, so projections legitimately move over time — that's the method working, not the indicator glitching.
The honest framing . Cycle analysis is a minority view of how markets work — the academic mainstream is skeptical that fixed-period cycles persist, and even practitioners regard Hurst's model as a probabilistic timing framework, not a prediction machine. Its best use is narrowing when to pay attention and stacking confluence with your other analysis; its worst use is treating a vertical line nine months out as an appointment price is obligated to keep. Nothing it draws is financial advice, and the further into the future a projection extends, the more decorative it becomes. אינדיקטור
AI Regime DetectionAI Regime Detection
Markov Regime Switching · 4-State Hidden Markov Model · Online Learning · Pine Script v6
This indicator uses a genuine machine learning model — a 4-state Hidden Markov Model with online learning — to classify the market into one of four regimes in real time: Bull Trend, Bear Trend, Ranging, and High Volatility. Instead of a binary “trend/no-trend” signal, it outputs a full probability distribution over all four regimes every bar, together with a confidence score, a live statistics dashboard, and the learned transition matrix.
Knowing the current regime is arguably the most important context in trading: trend-following systems bleed in ranging markets, mean-reversion systems get destroyed in strong trends, and position sizing should shrink when volatility explodes. This tool answers the question “what kind of market am I in right now — and how sure can I be?” using a probabilistic framework rather than fixed thresholds.
How It Works
The engine is a Markov Regime Switching model processed with Bayesian forward filtering (Hamilton filter) on every bar:
Four bounded, scale-free features are extracted each bar: trend correlation (price vs. time, −1 to +1), RSI-based momentum, volatility percentile rank, and Sharpe-normalized drift. Because all features are bounded and scale-free, the model behaves consistently across any symbol and timeframe — no re-tuning needed between a large-cap stock and a crypto pair.
Each regime is defined by an emission template describing what its features typically look like (e.g. Bull Trend expects positive trend correlation and positive drift; High Volatility expects a top-decile volatility percentile).
Every bar, the model computes the likelihood of the observed features under each regime using a Lorentzian kernel (fat-tailed, robust to outliers — the same distance philosophy popularized by Lorentzian Classification) or a Gaussian kernel, then updates the posterior probabilities through the Markov transition matrix.
Online learning (approximate online EM): the transition matrix and the emission means are continuously updated from the data itself, with a learning-rate control. The model adapts to the statistical personality of each symbol instead of staying frozen at its priors. Regularization (diagonal cap, off-diagonal floor, template anchoring) prevents the two classic HMM failure modes: regime lock-in and label switching.
The regime with the highest posterior probability becomes the detected regime; its probability is the confidence score. The filtering is strictly causal — only past and current bars are used, and regime-change labels are drawn on confirmed bars only, so the tool does not repaint.
The model was validated on Monte Carlo simulations with known ground-truth regimes (drift processes for trends, mean-reverting Ornstein–Uhlenbeck processes for ranges and volatility shocks) before release.
Features
Real-time regime classification: Bull Trend ▲, Bear Trend ▼, Ranging ◆, High Volatility ⚡
Full posterior probability for all four regimes every bar, not just a single label
Confidence score (0–100%) with visual probability bars
Chart background tinted by regime, opacity scaled by confidence
Non-repainting regime-change labels printed on the price chart
Confidence & probability oscillator pane with reference levels (uniform prior 25%, high-confidence 80%)
Statistics dashboard: current volatility & its percentile, trend correlation, regime age, average regime duration, average return per bar inside the current regime, total regime switches, time distribution across regimes
Live learned transition matrix (4×4) — see the actual switching probabilities the model has learned for your symbol
Next likely regime — the most probable transition out of the current regime
Long-run π — the stationary distribution: the share of time each regime is expected to occupy in the long run
Choice of Lorentzian (robust) or Gaussian emission kernel
5 built-in alerts: any regime change + one per specific regime
Settings
Model — Markov Regime Switching
Regime persistence (prior): initial probability of staying in the same regime bar-to-bar. Higher = smoother, fewer switches; lower = more reactive.
Learning rate — transition matrix: how fast the switching probabilities adapt to the symbol. 0 disables adaptation.
Learning rate — emission: how fast regime feature profiles adapt. 0 disables adaptation.
Online learning (adaptive): master switch for all learning; off = fixed prior model.
Emission kernel: Lorentzian (robust, default) or Gaussian.
Features
Trend correlation length: window for the price-vs-time correlation trend measure.
RSI momentum length: period of the momentum feature.
Realized volatility length: window for realized volatility.
Volatility percentile window: lookback used to rank current volatility (also the warm-up length).
Drift smoothing length: smoothing window for the normalized drift feature.
Appearance
Toggles for background coloring, dashboard, regime-change labels, and transition matrix rows.
Dashboard position & text size.
Custom colors for each of the four regimes.
Usage
When the model detects a Bull Trend regime with high confidence, the background turns green and a label marks the transition bar. This is the environment where trend-following entries, pyramiding, and letting winners run have a statistical tailwind. The confidence reading matters: an 85% Bull reading and a 45% Bull reading are very different market states — the dashboard’s probability bars show how much weight the competing regimes still hold.
In a Ranging regime, the probability pane typically shows the blue Ranging line dominating while trend probabilities stay suppressed. This is where breakout trades fail most often and mean-reversion (fading moves back toward the middle of the range) performs best. A falling confidence during a mature trend regime often precedes the transition into Ranging — watch the oscillator pane for the crossover of probability lines.
The High Volatility regime fires when volatility jumps into its top percentiles regardless of direction. This regime is a risk filter first and foremost: reduce position size, widen stops, or stand aside. High Vol regimes frequently appear at capitulation lows and blow-off tops, so their resolution (which regime follows) is informative — the “NEXT LIKELY” row of the dashboard shows the model’s learned expectation.
The dashboard is the statistical summary of everything the model knows. The transition matrix rows read left-to-right as “from the row’s regime, probability of moving to ▲ ▼ ◆ ⚡”. A learned matrix with strong diagonals means the symbol has persistent, tradable regimes; weak diagonals mean choppy regime behavior — itself useful information for strategy selection. LONG-RUN π tells you the personality of the instrument (e.g. an index that spends 60% of its time trending vs. a pair that ranges 70% of the time). Ø RET/BAR shows the realized average return per bar inside the current regime on this chart — a quick sanity check that the regime labels align with actual profitability.
The lower pane plots confidence as a colored area (colored by the ruling regime) plus all four probability lines. Regime transitions appear as probability crossovers, and the 80% dotted line marks the high-confidence zone. Time spent below ~45% confidence indicates a contested, transitional market — a reasonable filter for standing aside.
Details for the Curious
The Hamilton filter recursion is αₜ(j) ∝ bⱼ(oₜ) · Σᵢ αₜ₋₁(i) · A , normalized each bar, where bⱼ is the emission likelihood and A the transition matrix.
Transition-matrix learning uses an exponentially weighted update toward the per-bar posterior transition distribution, weighted by the previous state probability — an O(1) approximation of online Baum–Welch.
Emission means are updated toward observed features weighted by the state posterior, with an anchor term pulling back toward the initial templates to keep regime identities stable.
The warm-up period equals the volatility percentile window (default 300 bars). On symbols with short history, reduce this input.
Limitations & Honest Notes
Per-bar classification of noisy financial data has an information-theoretic ceiling; expect occasional flicker near regime boundaries and during genuinely ambiguous markets. The persistence prior and confidence threshold are the tools to manage this.
Probabilities are model outputs, not guarantees. A regime model describes the statistical character of recent price action; it does not predict news, gaps, or structural breaks.
This is a context / filter tool, not a standalone entry-exit system. It is designed to tell you which strategy the current market rewards, not to replace one.
Conclusion
AI Regime Detection brings a real, transparent machine learning pipeline — Hidden Markov Model, Bayesian filtering, Lorentzian likelihoods, and online EM adaptation — natively into Pine Script, with every internal state (probabilities, transition matrix, stationary distribution) exposed on the chart instead of hidden behind a black box. Use it to align your strategy with the market’s current regime and to size risk with the model’s own confidence.
אינדיקטור
אינדיקטור
CTZ Cycle Trader v1.6 CTZ Cycle Trader
A complete multi-asset cycle timing system that automatically detects Daily, Weekly, Yearly and Long Cycle lows, projects when the next lows are due, and tells you exactly where you are in every cycle at a glance.
WHAT IS CYCLE THEORY
Markets don't move randomly — they breathe in rhythmic cycles of accumulation and decline, each measured from one low to the next. Cycle analysis tracks these rhythms across nested timeframes: short daily cycles sit inside larger weekly cycles, which sit inside yearly and multi-year cycles. When several cycle lows fall due in the same zone, the biggest turning points form. This indicator automates the entire process that cycle traders have historically done by hand.
THE FOUR CYCLE TIERS
Daily Cycle Lows (DCL) — the short-term rhythm, your timing tool for swing entries. Each confirmed low prints with the day count of the completed cycle so you can track rhythm and symmetry at a glance.
Weekly Cycle Lows (WCL) — the medium-term structure. Marked with the week count between lows, these are the reversals that define swing and position trades.
Yearly Cycle Lows (YCL) — the macro turning points that anchor longer-term positioning.
Long Cycle Lows — the generational lows. Four years on Bitcoin and equities, eight years on gold, configurable for any asset.
MULTI-ASSET BY DESIGN
Every market has its own heartbeat, and the indicator maps to each one. Three modes in settings:
Auto-Detect — recognises the chart symbol and loads the right cycle lengths automatically. Bitcoin and Ethereum run 54–66 day daily cycles and 24–34 week weekly cycles with the 4-year long cycle. Stock indices (SPX, NDX, DJI) run 36–44 days and 22–31 weeks. Gold and silver run 22–28 days, 20–26 weeks and the 8-year long cycle.
Asset Class — pick Stocks, Metals, Bitcoin/Crypto, Forex or Energy from a dropdown and the full profile applies to any chart.
Manual — set every range yourself for fine-tuning or unusual assets.
SMART CONFIRMATION LOGIC
Lows aren't guessed — they're confirmed. A potential low becomes confirmed only when price recovers above the confirmation average. If price later breaks below a confirmed low, it's cancelled, and the marker relocates to the true low when it forms. Lower lows within a cycle window always supersede, so markers end up on the real bottom, not the first bounce.
FUTURE CYCLE LOW WINDOWS
The core edge: the indicator projects forward timing windows showing where the next DCL, WCL and Long Cycle low are statistically due — as chart zones and as actual date ranges on the dashboard, e.g. "Next WCL due: 24 Jul – 02 Oct". You know in advance when to be patient and when to be paying close attention.
LIVE DASHBOARD
Always-on panel showing your position in every cycle simultaneously: days since the last DCL, weeks since the last WCL, YCL and long cycle low, pending unconfirmed lows, whether price is currently inside a timing window, and the projected due dates for the next weekly and long cycle lows.
HOW TO USE IT
Apply to the daily timeframe. Check the dashboard to orient yourself — early in a cycle favours holding with the trend; late in a cycle, tighten risk and watch for the window. When price enters a timing window, watch for a swing low to form and confirm — that's the highest-probability turning zone. The real power is confluence: when a daily window opens inside a weekly window, and the weekly sits inside a long cycle window, the nested structure is pointing at a major low. Alerts cover confirmed and cancelled lows and window entries, so the indicator watches the clock while you live your life.
Best on daily charts. Works on crypto, indices, metals, forex and commodities.
DISCLAIMER
Cycle windows are probability zones based on historical rhythm, not guarantees. This indicator is for educational and research purposes and is not financial advice. Always do your own research and manage risk.
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