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
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MTF Range Tracker+ (M1D)OVERVIEW
MTF Range Tracker+ draws the Daily, Weekly and Monthly trading ranges as clean, connected boxes directly on your chart, then projects each range's High, Low and Equilibrium into a compact Power-of-Three (PO3) candle stack on the right. It adds Average Daily / Weekly / Monthly Range levels (ADR / AWR / AMR) and a small dashboard that tells you, at a glance, how much of each average range the current period has already used.
It is a top-down, time-based framework tool. Instead of hunting individual signals, it lays out the higher-timeframe structure — where price is inside its daily, weekly and monthly range (premium vs discount), how much room is statistically left, and which levels are acting as liquidity or as a magnet — so you can build a bias and plan trades around it.
Everything is drawn on bar close and completed ranges do not repaint.
WHAT IT PLOTS
Period range boxes (Daily / Weekly / Monthly) — each completed period is boxed from its high to its low across its own bars. Consecutive periods share their vertical dividers, so a run of days (or weeks, or months) reads as one connected structure rather than separate rectangles. The current, still-forming period is drawn live and left open on the right so it visibly flows into the projection.
Range projection to the PO3 candles — the window High and window Low (the highest high and lowest low across the periods currently shown) are drawn from the exact origin candle where each extreme formed, straight across to a compact PO3 candle that represents the range.
PO3 candle stack — each displayed period is also rendered as one compact candle to the right of price, grouped by timeframe (Daily, then Weekly, then Monthly) — a fast higher-timeframe read without leaving your execution chart.
ADR / AWR / AMR levels — the Average Daily, Weekly and Monthly Range is projected from the current period's open as +/- the full average, with optional +/- 1/3 levels.
Dashboard (M1D™) — a small monospace table showing, per timeframe, the percentage of the average range already used this period and the average range itself in points.
KEY DEFINITIONS
Equilibrium (EQ) — the 50% level of a range. Above EQ is a PREMIUM (relatively expensive) area; below EQ is a DISCOUNT (relatively cheap) area. This premium/discount read is the backbone of building bias.
ADR / AWR / AMR (Average Daily / Weekly / Monthly Range) — the average of the last N completed period ranges (high minus low). ADR answers "how far does this market usually travel in a day?" AWR and AMR answer the same for a week and a month. Lengths are adjustable.
Used % (dashboard) — how far the current period has already travelled relative to its average range: (this period's high − low) / average range × 100. Example: "1D 58%" means today has already covered 58% of a typical daily range. A low reading means the period still has room to expand; near or over 100% means it's already extended for its type, and the value turns to the Low colour past 100% as a visual flag.
HOW TO USE IT
Monthly bias (the widest context)
Is price in the monthly PREMIUM (above MEQ) or DISCOUNT (below MEQ)? That frames whether you are, broadly, looking to sell rallies or buy dips within the monthly range.
MH and ML are the monthly liquidity extremes — obvious targets and obvious places for stops to rest.
The monthly Used % tells you whether the month is early (room to run) or already stretched.
Weekly bias (the swing context)
Same premium/discount logic against WEQ. A weekly discount that aligns with a monthly discount is a stronger location to look for longs, and vice-versa.
WH / WL frame the week's liquidity; AWR frames how much more the week can reasonably travel.
Daily bias and trade planning (the execution context)
Use the previous day's DH / DL as liquidity references and DEQ as a common draw / target.
Use ADR to plan realistic targets: if only ~40% of the ADR is used and price is in discount below DEQ, a move back toward DEQ or the ADR+ level is a measured objective. If ~90% of the ADR is already used, expectations for further same-direction travel should be lower.
The +/- 1/3 ADR levels give intraday interim objectives and areas where extended moves often pause.
Reading the PO3 stack
Glance at the daily PO3 candles for the recent daily rhythm (expansion vs consolidation, up-closes vs down-closes) and at the weekly / monthly candle for the dominant higher-timeframe direction — all without switching charts.
A simple top-down routine
Monthly: note premium/discount and month range used.
Weekly: note premium/discount and where price sits vs WH / WL.
Daily: check ADR used and whether price is reaching for DH / DL or drawing back to DEQ.
Drop to your execution timeframe and take entries only in the direction and location the higher-timeframe ranges support.
SETTINGS
Ranges — toggle Daily / Weekly / Monthly and set how many completed periods to show (Days 1–10, Weeks 1–3, Months 1–2). The forming period always draws.
Range Style — box outline, High / Low / EQ colours (blue high / red low by default; set both to black for a fully neutral chart), and whether to connect the ranges to the PO3 candles.
PO3 Candles — show/hide, offset, width, spacing, wick width, per-cluster timeframe tag, EQ tick, and the bull/bear body / border / wick colours.
Average Ranges — enable ADR / AWR / AMR lines, set each averaging length, and toggle the 1/3 levels.
Dashboard — show/hide, position, text size.
Text — compact labels and independent size controls for the per-box and the projection / average labels.
HOW IT IS CALCULATED (and repainting)
Period ranges are captured natively from the chart: on each Daily / Weekly / Monthly rollover the completed period's high, low, open and the bars where its high and low printed are stored, then a new period starts. Completed boxes are fixed and do not repaint.
The weekly period is anchored to the weekend reopen (the Sunday session), so a single mid-week market holiday will not split a week into two; daily and monthly periods roll on their normal calendar boundaries.
ADR / AWR / AMR use confirmed higher-timeframe values (previous completed bar), the standard non-repainting approach.
Because monthly and weekly boxes need enough chart history to cover those periods, run the tool on an intraday-to-daily timeframe with sufficient loaded history (best on 15-minute charts and higher).
NOTES & DISCLAIMER
This indicator is an analytical and planning tool. It does not generate buy/sell signals, does not predict future price, and makes no representation about trading performance. Average-range statistics describe typical past behavior and can be exceeded or undershot at any time. Nothing here is financial advice — always do your own analysis and manage risk. Use it as one input in your own process. אינדיקטור
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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.
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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.
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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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Aquila Price Levels - Multi-Timeframe Institutional Levels 🦅 Aquila Price Levels - Multi-Timeframe Institutional Levels
The "Aquila Price Levels v1.1" script is a structural analysis tool developed to simultaneously map and visualize critical price levels across Daily (D), Weekly (W), and Monthly (M) timeframes directly on the operational chart.
The Importance of a Unified Visualization (Single Board):
Having a comprehensive overview of macro and micro levels in a single interface is critical for reading Order Flow and market structure. This centralized approach eliminates noise and the constant need to switch timeframes, allowing the user to:
Identify Confluences: Highlights zones where levels from different timeframes (e.g., Previous Week High and Current Daily Open) intersect, defining high-probability order blocks.
Map Liquidity: Makes external liquidity targets (PDH, PDL, weekly and monthly highs/lows) immediately visible. These are the primary targets exploited by algorithms and institutional players for positioning.
Define the Bias: Evaluating the real-time price position relative to macro Opens provides an objective reading of both short-term and long-term directional bias.
Manage Equilibrium Areas: Tracking the medians (H+L)/2 provides constant reference points for mean reversion setups.
Main Features:
Multi-Timeframe Tracking (Current & Previous): Automatic calculation and plotting of Open, High, Low, Close, and Median for the day, week, and month (both currently updating and previously consolidated).
Smart Label Management: The system dynamically groups labels on the horizontal axis if levels fall within a configurable tolerance threshold, preventing visual overlapping on the chart.
Summary Table (Dashboard): An integrated visual matrix (freely positionable) that summarizes the exact numerical values of all D/W/M levels, acting as an immediate control panel.
Operational Tooltips: Hovering over the price labels provides technical descriptions of the level's significance (e.g., directional watershed, macro wall, liquidity trap).
UI Customization: Total control over line thickness, styles, opacity for current periods, and label offsets.
Practical Application:
Particularly optimized for highly technical and volatile assets like XAUUSD (Gold), where millimeter precision on historical liquidity grabs and reactions to macro levels dictates the profitability of the operational setup.
🦅 Royal Eagles - Born to fly, born to dare. אינדיקטור
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CTZ Bitcoin Cycle Master (Modified)Here's a description written in your own words for the TradingView publish page, with the required credit to the original author since it's a modification of an open-source script:
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CTZ Bitcoin Cycle Master (Modified)
This is a modified version of the open-source Bitcoin Cycle Master by InvestorUnknown, republished under the Mozilla Public License 2.0 with full credit to the original author. The underlying on-chain models are unchanged — this version adjusts how the bands are positioned and adds user control over every line.
WHAT IT DOES
The indicator plots five long-term valuation models on the Bitcoin chart, designed for macro cycle analysis on high timeframes (weekly and monthly recommended, log scale):
Top Cap — a 35x multiple of Average Cap (the cumulative average of price over Bitcoin's lifespan). Acts as the upper boundary for speculative cycle peaks.
Terminal Price — derived from Coin Days Destroyed and normalised by Bitcoin's 21 million supply cap. A supply-adjusted price model historically relevant near cycle tops.
Realized Price — Realized Cap divided by circulating supply. The average on-chain cost basis of all coins, and a key line in bear market bottoms.
CVDD — Cumulative Value Coin Days Destroyed. A historically reliable floor model that has caught major cycle lows.
Balanced Price — Realized Price minus Transferred Price. A deep-value zone that has marked bear market capitulation lows.
WHAT'S DIFFERENT IN THIS VERSION
1. Recalibrated band positioning. Historical cycle behaviour shows diminishing returns — each cycle tops further below the classic upper bands. This version repositions three lines by default: Terminal Price sits 33 percent lower, CVDD 10 percent lower, and Balanced Price 5 percent lower than the original calculations.
2. Per-line offset multipliers. Every model has its own multiplier input, so you can shift any band up or down from the settings panel without touching code. Defaults reflect the recalibration above, but everything is fully adjustable back to the original values (set all multipliers to 1.0).
3. Delta Top removed. Stripped out to reduce chart clutter and focus on the models with the most consistent historical track record.
4. Full colour control. Each line has its own colour picker, so the indicator can be themed to any chart setup.
5. Converted to Pine Script v6.
HOW TO USE IT
Best viewed on INDEX:BTCUSD, weekly or monthly timeframe, logarithmic scale. Price approaching the upper bands (Top Cap, Terminal Price) has historically coincided with late-cycle euphoria and distribution. Price reaching the lower bands (Realized Price, CVDD, Balanced Price) has historically marked deep value and accumulation zones.
Data sources: Coin Metrics realized cap, Glassnode supply and transfer volume, INDEX:BTCUSD price history.
DISCLAIMER
This indicator is for research and educational purposes only and is not financial advice. On-chain models describe historical behaviour and offer no guarantee of future performance.
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Two notes before you publish. TradingView house rules require open-source mods to stay open-source and credit the original, which this description does in the first line — keep the attribution in the code header too. And if this one is staying in the CTZ private collection rather than being published, you can drop the licence paragraph and just use the description from WHAT IT DOES downward. אינדיקטור
Silver Bullet & First/Last FVGIt is designed around the popular ICT (Inner Circle Trader) "Silver Bullet" concepts. Its main purpose is to highlight specific time-based trading windows on your chart and automatically detect and isolate the most significant Fair Value Gaps (FVGs) that form within those windows.
Here is a breakdown of its functionality:
1. Specific Time Sessions
The script monitors three specific 1-hour time windows (defaulting to New York time, but adjustable):
London Silver Bullet: 03:00 - 04:00
New York AM Silver Bullet: 10:00 - 11:00
New York PM Silver Bullet: 14:00 - 15:00
Each of these sessions can be toggled on/off individually, and their border colors customized.
2. Session Range Highlighting
When one of these 1-hour sessions begins, the script starts tracking the absolute Highest and Lowest price reached during that hour.
Once the session ends, it draws a large, semi-transparent box encapsulating that entire 1-hour price action range.
The box is labeled in the bottom right corner (e.g., "Lon SB" or "NY AM SB") so you can easily visually identify the Silver Bullet hour in hindsight.
3. First and Last FVG Detection
This is the most unique feature of the script. While standard indicators highlight every FVG, this script filters them based on the Silver Bullet sessions:
It continuously looks for standard 3-candle Fair Value Gaps (both bullish and bearish).
However, it only plots FVGs if they occur inside one of the active Silver Bullet sessions.
Furthermore, to reduce clutter, it only stores and plots the First FVG and the Last FVG that formed during that specific 1-hour window.
It automatically extends the boxes of these specific FVGs to match the right edge (end time) of the Silver Bullet session box.
4. Memory and Optimization
To prevent TradingView from throwing "too many drawings" errors or causing lag on your chart:
It uses a custom data structure (SBSessionData) to manage the state of each session cleanly.
At the start of every new day, it runs a cleanup function (clearDrawings()) that deletes older session boxes and FVGs if they exceed the user-defined sb_lookback limit (default 100 historical boxes). אינדיקטור
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CTZ Bitcoin Vector Regime Tops & BottomsTwo frameworks. One chart. Cycle timing tells you when a low is due — regime analysis tells you whether the market agrees. v3.3 fuses them.
The Cycle Engine tracks Bitcoin's rhythm across four nested cycles — Daily (~30 days), Intermediate (~80 days), Yearly (~365 days), and the 4-Year cycle — detecting each low as it forms, learning from actual cycle lengths, and projecting forward: cycle lines, projection boxes with price targets, countdown timers, and progress bars for every degree. Star-rated confidence on every DCL and ICL (divergence, volume, regularity, translation), cycle failure detection with bull/bear context, invalidation levels, win/fail streaks, and multi-cycle sync detection.
The Vector Engine runs a six-component regime model alongside — trend structure, momentum, MACD, rate of change, drawdown, and Supertrend — scored into a composite that classifies the market as Strong Risk-On, Risk-On, Risk-Off, or Strong Risk-Off, with a live count of how many internals are improving. The regime also powers smarter bull/bear detection for the cycle engine's failure logic (toggleable).
Where they agree is where it matters:
⚡★ CONFLUENCE LOW — a cycle timing window is active and the Vector confirms: deep capitulation, internals turning up together, composite rising. The clock says a low is scheduled; the internals say it's actually forming.
⚠ V-TOP — the regime flips Risk-On → Risk-Off within bars of a fresh cycle high while translation is weak. Timing and condition both warning at once.
A full dashboard covers everything: cycle progress for all four degrees, translation, MA breakout status, upcoming low countdowns, zone alerts, invalidation prices, signal quality, and a dedicated Vector section with regime, score, and improvement breadth.
Comprehensive alerts: confluence signals, new cycle lows, high-conviction setups, cycle failures, sync events, zone entries, and MA breakouts.
Designed for BTCUSD daily.
Cycle projections and regime signals describe probabilities, not certainties. Not financial advice. אינדיקטור
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MR8 Trend Direction & Signal IndicatorThe MR8 is a dynamic trend-following indicator built on the McGinley Dynamic moving average — one of the most responsive and self-adjusting smoothing algorithms available. Unlike traditional EMAs that can lag or whipsaw in changing market conditions, the McGinley Dynamic automatically adapts its speed based on market velocity, resulting in cleaner, more reliable signals.
How It Works
MR8 plots two McGinley Dynamic lines — a faster Ribbon 8 and a slower Ribbon 9. When the faster line crosses above the slower line, the ribbon turns white, signaling bullish momentum and a potential long entry. When the faster line crosses below, the ribbon turns grey, signaling bearish momentum and a potential short entry. This crossover method filters out the noise and false flips that plague single-line slope-based indicators.
Built-In Stop Loss
MR8 includes an optional visual stop loss line calculated directly from the ribbon's current value — 2% above the line for shorts, 2% below for longs. Toggle it on in settings to see exactly where your risk level sits relative to the indicator itself, on any timeframe.
Alert Ready
MR8 includes two built-in alert conditions — one for long signals and one for short signals — with a webhook-compatible JSON message format. Connect directly to any automated trading bot or notification system with zero additional configuration.
Best Used On
BTC/USD and BTC/USDT
55 minute, 1 hour, and higher timeframes
Futures and spot markets
Settings
Ribbon 8 Length — controls the speed of the faster line (default 12)
Ribbon 9 Length — controls the speed of the slower line (default 21)
Stop Loss % — distance from the ribbon for the optional SL line (default 2%)
Show Stop Loss Line — toggle the SL visualization on or off אינדיקטור
