COT Trend [XWiseTrade]Visualize institutional bias using Commitment of Traders (COT) data.
This indicator compares non-commercial net positions of the current symbol against the USD Index to automatically determine market bias:
• Green background = Speculators more long than USD → Bullish
• Red background = Speculators more short than USD → Bearish
Supported symbols: Major FX pairs, Gold, Silver, Oil, SPX, NDX.
Features:
• Weekly COT data via official LibraryCOT
• Clear background coloring
• Persistent bias label
• Works on any timeframe
Perfect for trend filtering and understanding "smart money" positioning.
More premium indicators and strategies coming soon at:
xwisetrade.com
Be Wise. Trade X.
Dec 22, 2025
Release Notes
Visualize institutional bias using Commitment of Traders (COT) data.
This indicator compares non-commercial net positions of the current symbol against the USD Index to automatically determine market bias:
• Green background = Speculators more long than USD → Bullish
• Red background = Speculators more short than USD → Bearish
Supported symbols: Major FX pairs, Gold, Silver, Oil, SPX, NDX.
Features:
• Weekly COT data via official LibraryCOT
• Clear background coloring
• Persistent bias label
• Works on any timeframe
Perfect for trend filtering and understanding "smart money" positioning. Indicator
P/E & Forward P/E vs History# P/E & Forward P/E vs History
## Overview
This indicator plots a stock's **trailing P/E** and an approximate **forward P/E** in a lower pane, then frames both against the stock's *own* valuation history using a mean line and standard-deviation bands. The goal is to answer a question a raw P/E number can't: not "is 22x expensive?" but "is this stock expensive **for itself**, relative to how the market has typically valued it?"
A P/E of 22 might be cheap for one company and rich for another. By comparing the current multiple to its historical mean and expressing the gap in standard deviations, the indicator turns an ambiguous absolute number into a relative, self-referential read.
## What it plots
- **Trailing P/E** (blue) — the real, reported multiple: price divided by trailing-twelve-month earnings per share.
- **Forward P/E** (orange) — a forward-looking estimate of the multiple. This is a proxy (see Limitations).
- **Mean P/E** (gray dashed) — the average trailing P/E over the chosen window.
- **±1σ band** (shaded) — one standard deviation above and below the mean. Roughly two-thirds of historical observations fall inside this zone.
- **±2σ lines** — two standard deviations out. Roughly 95% of history falls inside ±2σ; readings beyond it are statistically unusual for the stock.
- **Info table** — a corner readout of the current trailing P/E, forward P/E, mean, the live **z-score**, and a plain-English "Position" verdict (Cheap / Normal / Rich, etc.).
## How it's calculated
**Trailing P/E.** TTM earnings per share is pulled from PulseWire's fundamental data, and the multiple is current price divided by that figure. You can choose diluted or basic EPS as the source. Bars where TTM EPS is zero or negative are left blank, since a P/E built on near-zero or negative earnings is not meaningful.
**Forward P/E.** Two proxy methods are offered:
1. *Analyst estimate (×4)* — the next-quarter analyst EPS estimate, annualized by multiplying by four.
2. *Growth assumption* — trailing TTM EPS grown forward by a user-set annual rate.
The forward multiple is then current price divided by the chosen forward EPS figure.
**Historical mean and bands.** Two windowing modes are available:
1. *All history* — a cumulative mean and standard deviation computed across every available bar, so the "normal" expands as more data accrues.
2. *Rolling lookback* — a moving mean and standard deviation over a fixed number of bars (default 252, about one trading year), which adapts to recent behavior.
**Z-score.** The current trailing P/E minus the mean, divided by the standard deviation. This single number says how many standard deviations above or below average the stock is trading right now. The "Position" label translates it: beyond +1σ reads as Rich, beyond −1σ as Cheap, beyond ±2σ as Very rich / Very cheap, and inside ±1σ as Normal.
## Settings
- **Trailing EPS source** — diluted (default) or basic. If one errors on a given ticker, switch to the other.
- **Show Forward P/E** — toggle the orange line.
- **Forward EPS method** — analyst-estimate (×4) or growth-assumption.
- **Assumed annual EPS growth %** — used only by the growth-assumption method.
- **Average window** — all-history or rolling lookback.
- **Rolling lookback (bars)** — window length when using rolling mode.
- **Show ±1σ / ±2σ bands** — toggle the bands.
- **Table position / text size** — placement and sizing of the info table.
## How to read it
Look at where the blue line sits relative to the shaded band rather than at its absolute level. Inside the band is ordinary. Pushing above +1σ means the market is paying more per dollar of trailing earnings than it usually does; dropping below −1σ means the opposite. The ±2σ lines mark the statistical extremes of the stock's own range. The z-score and Position label in the table give you the same read as a number and a word, so you don't have to eyeball it.
The gap between the orange and blue lines is also informative: a forward multiple well below the trailing one implies the market expects earnings to grow (a larger future denominator shrinks the multiple). If the average line is slowly drifting higher over time in all-history mode, the market has structurally re-rated the stock to a richer multiple — the definition of "normal" has moved.
## Limitations
**Forward P/E is an approximation, not a true consensus number.** Pine Script does not expose a forward twelve-month consensus EPS. The two proxy methods here are deliberate simplifications: the ×4 annualization ignores seasonality, and the growth method is only as good as the rate you assume. Treat the forward line as directional, not as a terminal-grade figure.
**Fundamental history depth is limited.** Available EPS history on the platform is finite and often spans only a handful of years, so the "all history" mean and bands cover only the data that exists — not a multi-decade record.
**Stocks only.** The indicator needs per-share earnings data. Indices, ETFs, forex, and crypto will show n/a.
**Earnings distortions.** When trailing EPS collapses toward zero around a loss quarter, the ratio can spike, go negative, or blank out. A dramatic move in the P/E line is sometimes an earnings artifact rather than a valuation event — check the earnings backdrop before reading too much into it.
## Disclaimer
This script is for research and educational purposes and is not financial advice. Fundamental data is provided as-is by the platform's data vendors and may contain gaps or errors. Always verify figures independently before making any decision. Indicator
Indicator
W & M Pattern | 3 Peaks + Liquidity Sweep | RR ToolW & M Pattern | 3 Peaks + Liquidity Sweep | RR Tool
This indicator identifies high-probability reversal setups by combining classical market structure analysis with liquidity sweep detection — two concepts widely used in Smart Money and Price Action trading.
How It Works
The indicator continuously scans the chart for two mirror-image setups:
Bullish W Pattern (Long Setup)
In a falling market, price forms three consecutive Lower Highs (LH1 → LH2 → LH3), confirming a bearish structure. The indicator then watches for a W formation — where price first drops to a swing low, sweeps below it to grab liquidity (the sharp wick down), and then reverses sharply upward forming the right leg of the W. This liquidity sweep is the key trigger, as it signals that smart money has absorbed sell-side orders and a reversal is likely. A long entry is signaled as price recovers, with the stop loss placed just below the W's sweep low and the take profit targeting either the 1st or 3rd Lower High.
Bearish M Pattern (Short Setup)
In a rising market, price forms three consecutive Higher Highs (HH1 → HH2 → HH3), confirming a bullish structure. The indicator then watches for an M formation — where price pushes above the prior swing high to sweep buy-side liquidity (the sharp wick up), then fails and drops below the neckline. This sweep signals that smart money has distributed into retail buying pressure and a reversal downward is likely. A short entry is signaled as price breaks down, with the stop loss just above the M's sweep high and take profit targeting the 1st or 3rd Higher High. Indicator
W & M Pattern | 3 Peaks + RR ToolW & M Pattern | 3 Peaks + Liquidity Sweep | RR Tool
This indicator identifies high-probability reversal setups by combining classical market structure analysis with liquidity sweep detection — two concepts widely used in Smart Money and Price Action trading.
How It Works
The indicator continuously scans the chart for two mirror-image setups:
Bullish W Pattern (Long Setup)
In a falling market, price forms three consecutive Lower Highs (LH1 → LH2 → LH3), confirming a bearish structure. The indicator then watches for a W formation — where price first drops to a swing low, sweeps below it to grab liquidity (the sharp wick down), and then reverses sharply upward forming the right leg of the W. This liquidity sweep is the key trigger, as it signals that smart money has absorbed sell-side orders and a reversal is likely. A long entry is signaled as price recovers, with the stop loss placed just below the W's sweep low and the take profit targeting either the 1st or 3rd Lower High.
Bearish M Pattern (Short Setup)
In a rising market, price forms three consecutive Higher Highs (HH1 → HH2 → HH3), confirming a bullish structure. The indicator then watches for an M formation — where price pushes above the prior swing high to sweep buy-side liquidity (the sharp wick up), then fails and drops below the neckline. This sweep signals that smart money has distributed into retail buying pressure and a reversal downward is likely. A short entry is signaled as price breaks down, with the stop loss just above the M's sweep high and take profit targeting the 1st or 3rd Higher High. Indicator
Indicator
Indicator
Indicator
Indicator
CTZ BTC ULTIMATE CYCLE [Fused+Simplified]
**CTZ BTC ULTIMATE CYCLE v3 — Description & How to Trade**
---
**WHAT THIS INDICATOR DOES**
CTZ BTC Ultimate Cycle v3 tracks Bitcoin's four natural market cycles simultaneously — the Daily Cycle Low (DCL), Intermediate Cycle Low (ICL), Yearly Cycle Low (YCL), and Four-Year Cycle Low (4YCL). Every BTC rally and correction follows rhythmic, repeating patterns. This script identifies those patterns in real time, marks where you currently are inside each cycle, projects where the next low is likely to land, and rates the quality of every signal with a confidence score.
Built on the Cycle Theory methodology (Loukas / CTZ framework), fused and simplified into a single overlay with one master sensitivity control instead of 20+ raw inputs.
---
**THE FOUR CYCLES**
🟢 DCL — Daily Cycle Low (~20–30 bars)
The smallest repeating rhythm. Used for short-term entry timing. Buy near the expected low, exit toward the subsequent cycle high.
🔵 ICL — Intermediate Cycle Low (~60–80 bars)
The bread-and-butter swing cycle. Contains 2–4 DCLs. Entries near an ICL low typically produce 20–50% moves before the next ICL arrives.
🟡 YCL — Yearly Cycle Low (~250–365 bars)
The annual rhythm. Contains 3–5 ICLs. YCL lows are major accumulation zones — deeper drawdowns that shake out weak hands before sustained runs.
🟣 4YCL — Four-Year Cycle Low (~900–1458 bars)
Bitcoin's dominant macro cycle, aligned with the halving cadence. A confirmed 4YCL is the highest-conviction long entry the indicator produces.
---
**WHAT YOU SEE ON THE CHART**
• Cycle low labels — DCL / ICL / YCL / 4YCL printed below each confirmed pivot, with a star rating (★★★★★) showing signal confidence
• Confidence stars — 1 to 5 stars based on RSI divergence, MACD divergence, above-average volume, cycle regularity, and right translation
• Projection boxes — shaded zones to the right showing the expected timing and price range of the next DCL and ICL low
• Invalidation lines — dotted lines at the prior cycle low price (DCL INV / ICL INV). A daily close below these levels means the cycle count has failed
• Translation label — LEFT / MID / RIGHT showing where the cycle high printed relative to the midpoint. Right = bullish. Left = bearish
• MA Breakout — a 10-bar MA re-cross confirmation after price dips below it. Confirms the cycle low is likely in
• ⚡ Cycle Sync — when a projected DCL and ICL converge within ±4 bars. These aligned lows tend to produce stronger reversals
• ⛔ Cycle Fail — printed in bull markets when a new low undercuts the prior cycle low (a genuine warning). In bear markets the same event prints a muted "Bear ↓" label instead — because undercutting is expected behaviour in a downtrend
• Status label — plain-English line on the chart: current cycle day, countdown to next low, translation, MA status, and zone alerts
• Dashboard (top right) — 3 sections: WHERE ARE WE (progress bars for all four cycles), WHAT TO WATCH (countdowns, zones, invalidation levels, sync), SIGNAL QUALITY (stars, divergence, regularity, failure risk)
---
**CYCLE HEALTH TRAFFIC LIGHT**
The very first thing in the dashboard is a single traffic light — the overall Cycle Health.
🟢 HEALTHY — Right-translated, MA confirmed, no failure risk. Trend is with you.
🟡 NEUTRAL — Mixed signals or approaching a timing window. Reduce size, watch closely.
🔴 CAUTION — Left-translated, overdue cycle, or price near the invalidation level. Be defensive.
---
**HOW TO TRADE IT**
Step 1 — Check the Regime
Read the Regime row in the dashboard. BULL = cycle failures are meaningful warnings. BEAR = lower lows are normal, don't buy Bear ↓ labels expecting a reversal.
Step 2 — Read the bigger cycles first
Check YCL and 4YCL progress. If either is overdue (progress bar over 100%, shown in red), a major low may be forming. Don't trade DCLs aggressively against an overdue YCL.
Step 3 — Wait for the projection zone
The dashboard shows ⚡ IN ZONE when price enters the expected timing window. This is not a buy signal on its own — it means the low could arrive now. Reduce size and start watching for confirmation.
Step 4 — Confirm with MA Breakout + stars
Once a cycle low label prints, wait for the 10-MA re-cross (dashboard shows ✓ MA Break). Only trade 4–5 star setups at ICL or YCL timeframes for highest-probability entries.
Step 5 — Place your stop below the invalidation line
The DCL INV and ICL INV dotted lines mark the price level that must hold. A daily close below either line means the cycle count is invalid — exit the trade.
Step 6 — Exit into the next projected high
Take partial profits when cycle progress approaches 80–90% of the expected length. Full exit before an ICL is due if translation is shifting left or a ⛔ Fail label appears on a smaller cycle within the current run.
---
**SETTINGS**
Sensitivity — Low / Medium / High
• Low: fewer signals, stronger pivots only. Best for clean, rare setups.
• Medium (default): balanced. Works well on the daily BTC chart.
• High: catches more lows including early ones. More signals, more noise.
Individual cycle toggles let you show/hide DCL, ICL, YCL, and 4YCL independently. Colours, alerts, projection boxes, the phase ribbon, and the status label are all separately toggleable.
---
**ALERTS INCLUDED**
• High-conviction DCL (RSI + MACD divergence confirmed)
• Cycle failure (bull market context only)
• Cycle sync imminent (DCL + ICL converging)
• Price entering projection zone
• MA breakout confirmed
• Webhook-ready alertconditions for DCL / ICL / YCL / 4YCL detection
---
**RECOMMENDED TIMEFRAME**
Daily chart, BTCUSD or BTCUSDT. The cycle lengths are calibrated specifically for Bitcoin's daily rhythm. Lower timeframes will produce noise; weekly is too slow to catch DCLs meaningfully.
---
**COMMON MISTAKES**
✖ Buying a Bear ↓ label as if it were a bullish entry — it is an expected continuation, not a reversal
✖ Entering before the MA breakout is confirmed — the low may not be in yet
✖ Trading DCLs when Cycle Health is red — you are fighting the dominant trend
✖ Holding through an ICL when translation has already shifted left — the cycle is weakening and lower lows are likely Indicator
Global Market Strength and Breadth StanceIntroduction
The Market Strength and Breadth Dashboard is a comprehensive, institutional-grade market monitoring tool designed for swing traders and active investors. Instead of trading in a vacuum, this dashboard scans the internal health of a chosen market across cap sizes, sector leaders, equal-weighted indices, and growth/value proxies. By analyzing multiple dimensions of trend strength and rolling them up into a live dashboard, the indicator calculates an overall Market Stance and provides actionable guidance on Total Open Risk (TOR).
Whether you trade in the US, India, Japan, China, Taiwan, or South Korea, this dashboard provides a top-down view of market breadth so you can trade with the wind at your back.
Key Features
1. Multi-Market & Sector Breadth Coverage
The dashboard automatically maps a curated list of index benchmarks, equal-weight indices, growth/tech proxies, and sector ETFs based on your selected country:
United States (US): SPY (S&P 500), QQQ (Nasdaq 100), RSP (S&P 500 Equal Weight), IWM (Russell 2000), MDY (S&P MidCap 400), SMH (Semiconductors), IGV (Tech-Software).
India (IN): Nifty 50, Nifty 50 Equal Weight, Nifty 500, Nifty Midcap 100, Nifty Smallcap 100, Nifty IT, Nifty Finance, Nifty Auto, Nifty Banking, Manufacturing, Nifty India Digital.
Japan (JP): Nikkei 225, TOPIX, TOPIX 100, TOPIX Mid 400, Nikkei Mid Small ETF, TOPIX Small Index, Nikkei Semiconductor, Semiconductor ETF, Electric Appliances, TOPIX Machinery.
China (CN): Total Stock Market, Top 300 Index (Weighted & Equal Weight), 50 Large Cap, 500 Mid Cap, 1000 Small Cap, ChiNext 100, Tech/Semis/AI/Biotech.
Taiwan (TW): TAIEX, Top 50 ETF, Mid-Cap 100 ETF, TPEX Weighted Index, Semiconductors Sub-Index, Electronics Sub-Index, Electronic Parts/Components, Market Leader Equal Weight ETF, IT Growth Equal Weight ETF.
South Korea (KR): KOSPI, KOSPI 200, KOSPI Large, KOSPI Mid, KOSPI Small, KOSDAQ, KOSDAQ 150, KOSPI 200 Equal Weight, KQ150 Equal Weight.
2. Timeframe-Adaptive Moving Averages
Moving average lengths are automatically adjusted based on your selected Analysis Timeframe to ensure the technical signals match the trend structure of that horizon:
Daily Timeframe: 20 SMA (Short-term), 50 SMA (Medium-term), 200 SMA (Long-term / Macro).
Weekly Timeframe: 10 SMA, 30 SMA, 40 SMA.
Monthly Timeframe: 3 SMA, 6 SMA, 10 SMA.
3. Advanced Hybrid Trend Engine
Rather than relying on a single moving average, the dashboard calculates a Hybrid Trend for each index by combining two distinct methodologies:
SMA Ribbon Trend: Evaluates alignment. A full bullish alignment requires:
Price > SMA 1 > SMA 2 > SMA 3, while a bearish alignment requires:
Price < SMA 1 < SMA 2 < SMA3
Donchian Channel Trend: Checks price relative to the 20-period Donchian mid-line. If the price is within 15% of the Donchian mid-line, the trend is treated as Sideways (congestion). If it breaks out above or below this corridor, it triggers a trend state.
The Hybrid Nuance: A ticker is only marked in an Uptrend if the Donchian trend is bullish and the SMA Ribbon is not bearish. It is marked in a Downtrend if the Donchian trend is bearish and the SMA Ribbon is not bullish. Otherwise, it is classified as Sideways.
4. Granular Status Classification
Every monitored index is evaluated and categorized into one of five states:
🟢 Very Bullish: Macro bullish (SMA 2 > SMA 3), short-term bullish (SMA1 > SMA2), price trading above the short-term SMA 1, and the Hybrid Trend is actively upward.
🟢 Bullish: Macro and short-term bullish alignments are in place, price is above
SMA 1, but the Hybrid Trend has turned sideways.
🔵 Pullback: Macro and short-term bullish alignments are intact, but price has pulled back below the short-term SMA 1 (while holding above the medium-term SMA 2). Ideal for dip-buying setups.
🟡 Caution: Signals are mixed. This occurs during transitional phases, such as when price is below SMA 2 in a macro uptrend, or when price trades above SMA 1 but the macro alignment is bearish (SMA 2 ≤ SMA 3).
🔴 Bearish: Macro bearish alignment (SMA 2 ≤ SMA 3) and the price is below its short-term
SMA 1.
The Breadth & Stance Engine (Dashboard Footer)
The bottom row of the dashboard acts as the command center, compiling all individual metrics into market breadth stats and a singular directional bias:
1. Market Stance & Total Open Risk (TOR)
The dashboard calculates a global market posture based on the state of the primary index (e.g., SPY for US, Nifty 50 for India) and the percentage of overall constructive indices:
Risk-On (Aggressive) | TOR Open (6-8R): The primary index is Bullish/Very Bullish, ≥ 70% of the market is constructive, and ≤ 10% is Bearish. This is the green light for aggressive long positioning.
Risk-On (Selective) | TOR Normal (4-5R): The primary index is constructive, and ≥ 50% of the market is constructive. Longs are favored, but selectivity and tight setups are required.
Risk-Off (Defensive) | TOR Tight (1-2R): The primary index is bearish or ≥ 50% of the indices are in a Bearish status. Capital should be defensively positioned; focus shifts to short exposure or hedging.
Capital Preservation | TOR Cash (0R): The primary index is Bearish, and ≥ 75% of all indices are in a Bearish status. The system advises sitting in cash.
Caution / Neutral | TOR Max 3R: Outlines range-bound or highly rotational conditions. Open risk should be strictly capped.
2. Breadth Ratio Columns
The dashboard displays raw breadth ratios for three structural checkpoints:
Price > MA1 (Short-term momentum breadth)
MA1 > MA2 (Medium-term structural health)
MA2 > MA3 (Long-term structural alignment)
Format: L / S (Long / Short). E.g., 5L / 2S means 5 indices are bullish on that metric, and 2 are bearish.
Color Coding: Automatically highlights in Green if ≥ 70% of the indices are positive, Red if ≥ 60% are negative, and Yellow for rotational/neutral conditions.
Under the Hood: Pine Script v6 Optimization
This script has been engineered to prevent chart lag. All calculations are requested dynamically using a single, optimized request.security tuple call per ticker.
No Repainting : The dashboard is calculated strictly on closed historical bars and the live real-time bar using barstate.islast, ensuring that historical data is not distorted and the dashboard is lightweight.
Declarative Layouts : The UI adapts row heights dynamically based on the number of active indices for the selected country, preventing empty table cells from wasting screen real estate.
User Input Settings
Active Market / Country : Switch between US, Korea, China, Taiwan, Japan, and India.
Analysis Timeframe : Select Daily, Weekly, or Monthly.
Table Position : Choose from 9 positions on your chart canvas.
Text Size : Small, Normal, or Large text configurations.
Styling & Colors : Fully customize table frames, title background, warning cells, risk stances, and text colors to match your dark or light chart theme.
⚠️ Important Caution & Risk Disclaimer
Please read and understand the following before incorporating this dashboard into your trading:
Index Decoupling: Sector weightings in modern index products are often heavily skewed toward mega-cap stocks. An index may print "Very Bullish" while the vast majority of individual mid-and-small-cap stocks are struggling. Always cross-reference index breadth with individual stock scans.
Breadth is a Filter, Not a Trigger: The dashboard's output (such as "Risk-On" or "Risk-Off") represents a statistical regime filter of market conditions. It is not a direct buy or sell signal. Trade execution must still rely on your own verified setups, trigger criteria, and risk-reward calculations.
Data & Calculation Lag: Because the dashboard aggregates multiple indices and ETFs, there may be temporary divergences in fast-moving markets or discrepancies between local index data feeds.
No Guarantee of Accuracy: Historical performance of these filters is not indicative of future results. Market regimes can shift rapidly without warning. You must use your own judgment, manage your trade sizing, and implement hard stops on every position. Never risk more capital than you can afford to lose. Indicator
Macro Liquidity Z-Score (Smoothed)Overview
The Global Liquidity Z-Score Index is a macro-analytical tool designed to track, smooth, and visualise the expansions and contractions of global fiat liquidity. Central bank interventions and monetary policy print the ultimate "tide" that lifts or lowers all risk assets. This indicator standardises global money supply expansion into a clean standard deviation oscillator (Z-Score), helping macro investors identify generational market bottoms and structural cycle peaks.
Unlike traditional economic charts that suffer from heavy month-to-month seasonal reporting noise, this script applies a dual-stage filtering system to isolate the true multi-year structural trend.
How It Works & Calculations
This indicator functions best when applied to a combined custom global M2 ticker string (such as summing the M2 figures of the US, Eurozone, China, Japan, and the UK).The calculation follows two distinct mechanical steps:
1. Seasonality Smoothing: Raw monthly macro data inherently has annual jagged noise due to holiday spending cycles and uneven central bank reporting dates. The script applies a localised Simple Moving Average (SMA) filter to smooth these short-term discrepancies.
2. Statistical Variance (Z-Score): The script then calculates the standard deviation of the smoothed liquidity trend against a long-term rolling baseline. The final formula plots how many standard deviations current global liquidity is deviating from its multi-year mean:
Z = ( x - µ ) / σ
Z = (Where x is the smoothed M2 data, µ is the rolling mean lookback, and σ is the standard deviation).
How to Use & Interpret the Signals
To align this script with major asset class cycles (like the 4-year crypto halving cycles or structural equity regimes), it is highly recommended to use it on the Monthly (1M) time frame with a Z-Score Lookback of 36 or 48 months.
• The Upper "Overheated" Threshold (+1.2 Zone): When the indicator line spikes deep into the upper band and turns red, global central banks are injecting capital at a rate significantly higher than the multi-year average. This represents peak monetary expansion, historically correlating with late-stage bull market euphoria and asset overvaluation. This is a zone to scale out of risk.
• The Lower "Liquidity Floor" Threshold (-1.2 Zone): When the indicator bottoms out into a deep valley and turns green, it highlights severe quantitative tightening or liquidity contraction relative to the trend. Historically, when the line stabilises in this zone and begins curling back upward, it signals a structural market pivot—marking exceptional, low-risk periods for long-term spot asset accumulation.
• The Current Regime: The baseline (0.0) represents perfectly neutral liquidity expansion. Watch for clean, rolling cross-overs of the baseline to identify mid-cycle momentum shifts.
Inputs & Customisation
• Source Data: Defaults to close. Ensure your active chart is loaded with a global M2 tracking formula.
• Seasonality Smoothing: Controls the short-term smoothing filter. Recommended setting: 3 to 6 months to erase reporting noise.
• Z-Score Lookback: Controls the multi-year statistical lens. Recommended setting: 36 to 48 months for macro market cycles.
Indicator
Interbank SessionsInterbank Sessions is a precision‑engineered timing tool designed for traders who rely on clean, repeatable intraday structure.
The indicator plots three vertical timelines representing the core global trading sessions:
Asia Session
London Session
New York Session
Built for Forex and cryptocurrencies, Interbank Sessions provides a clear visual framework for understanding liquidity cycles, volatility rotations, and session‑to‑session transitions.
Traders in cash indices and equities can also use it to mark the cash opens of Asia, Europe, and the United States — giving you a unified, global market timing map on any chart.
Every element is fully customizable:
Adjustable session times for any timezone
Custom colors, line styles, and label visibility
Minimalist, non‑intrusive vertical markers
Works on all timeframes and all assets
Interbank Sessions delivers a clean, institutional‑grade view of the market’s temporal rhythm — without clutter, noise, or unnecessary features. Indicator
[3Commas] POL RSI Reversal DCA - Short Indicator POL RSI Reversal DCA - Short Indicator
🔷 What it does:
This is a signal-only indicator that mirrors a short-side mean-reversion workflow on POL / USDT. It tracks one virtual short position at a time, opened when the 5-minute RSI(9) crosses down through 80 (overbought momentum rollover). Up to three averaging orders fill at fixed deviations ABOVE base entry (+1%, +2%, +3%) with uniform sizing. Exit is a 1.3% Take Profit with a 0.3% trailing retrace, plus a hard 8% Stop Loss. The indicator computes running average entry, deployed capital, open PnL, and lifetime realized PnL — all from honest fill-by-fill bookkeeping. Every event emits a webhook-ready JSON alert payload for direct DCA Bot consumption.
- Momentum-exhaustion trigger: 5m RSI(9) crossing DOWN through 80.
- Uniform DCA ladder: +1% / +2% / +3% above base entry, equal sizing.
- Tight 1.3% Take Profit with a 0.3% trailing lock, and a hard 8% Stop Loss.
- Honest virtual bookkeeping: Open PnL and lifetime Total PnL displayed live on the chart.
🔷 Who is it for:
- Intraday traders fading overbought spikes on POL on lower timeframes.
- Bot operators who want a chart-driven signal source that emits per-event JSON ready for a DCA Bot.
- Traders who want a defined-risk short signal — modest averaging plus a hard stop — rather than an open-ended martingale.
- Operators tracking staged position management (entry, up to three averaging fills, single exit) directly on the chart without the strategy-tester overhead.
🔷 How does it work:
Entry Trigger: A 5-minute RSI(9) is sampled via request.security with lookahead disabled (no repaint). The base short opens when that RSI crosses DOWN through 80 — the prior 5m close was ≥ 80 and the current is below it, marking the moment overbought momentum rolls over.
Base Entry: When the trigger fires, the indicator marks a virtual short, captures the base entry price, and seeds the cost-basis ledger with the configured base order size (default 500 USDT).
Averaging Orders (Uniform DCA Ladder): After base fill, the indicator monitors price deviation above the base entry. Each averaging order has a fixed deviation — +1%, +2%, +3% — with uniform sizing (250 USDT each). Each fill updates the running cost-basis and dispatches its own webhook payload, raising the virtual average entry.
Honest Virtual Bookkeeping: Total cost and qty are updated incrementally on every event, so the avg entry, deployed capital, Open PnL, and Total PnL displayed in the status table reflect the actual broker-equivalent position state — no shortcut from base entry, no synthetic averaging.
Exit (TP + Trailing): A 1.3% Take Profit below the running average entry arms a trailing exit. Once price trades through the TP level, the indicator tracks the in-favor low and signals a close when price retraces 0.3% off that low.
Stop Loss: A hard 8% Stop Loss above the average entry. If price runs against the short past that level, the close webhook fires, realized PnL accumulates, and the virtual position resets.
Lifetime Total PnL: When a cycle closes, its realized PnL accumulates into a lifetime counter. The status table displays both Open PnL (current cycle, resets on exit) and Total PnL (lifetime, persists across chart history).
🔷 Why it's unique:
- Momentum-Exhaustion Trigger: Rather than signaling on any overbought reading, the short opens specifically on the RSI crossing DOWN through 80 — the rollover moment — filtering out signals that fire while momentum is still climbing.
- Defined-Risk DCA: A modest 3-rung uniform ladder AND an 8% hard stop, so the worst-case loss per cycle is bounded and known in advance.
- Trailing Take Profit: The 1.3% target arms a 0.3% trailing exit rather than a fixed limit — capturing the reversion snap and then riding any follow-through.
- Lifetime PnL Tracking: Open PnL and Total PnL are displayed live on the chart — strategy-tester-equivalent insight without running a backtest.
- Per-Event Webhook Ledger: Up to six discrete events per cycle (entry + 3 AO fills + TP or SL), each with its own JSON alert payload. One PulseWire alert with "Any alert() function call" drives a DCA Bot end-to-end.
🔷 Considerations Before Using the Indicator:
Sample Size: The companion strategy's backtest produced 87 closed trades — just below the ~100-trade floor commonly used for statistical relevance. The high win rate and profit factor reflect favorable conditions over the test period; treat them as indicative, not a forward-performance guarantee.
Short Execution Venue: This signals shorts. Live shorting of POL requires a margin or perpetual venue — it cannot run on a spot account.
Lower-Timeframe Sensitivity: The trigger runs on a 5-minute RSI. Lower timeframes generate more signals but are more sensitive to noise and fees. Confirm trade frequency and fee drag fit your execution venue.
Stop Loss Discipline: The 8% Stop Loss is the defining risk control. With base plus three averaging orders, maximum deployed capital is ~1,250 USDT (12.5% of the default reference equity); an 8% stop on that bounds the worst-case loss to roughly 1% of equity. Keep the stop enabled — removing it converts this into an unbounded martingale short.
Trend Risk: Fading overbought conditions works best in ranges and choppy regimes. In a strong sustained uptrend the short can hit the 8% stop repeatedly. The RSI-crossing-down trigger reduces but does not eliminate this.
Cross Detection Granularity: Entries, AO fills, and exits are evaluated on bar close. A bar that spikes through a level and returns within the same bar may be missed by design — this matches realistic polling behavior and avoids over-signaling on intra-bar wicks.
Live vs Historical State: The virtual position state is rebuilt from chart history each time the indicator is recompiled. If added mid-deployment or if the live bot diverges (manual interventions, partial fills), the indicator state may not match the live bot. Toggle the indicator off and on to reset.
Backtesting Note: This is an indicator, not a strategy. There is no built-in P&L tester — but the live Total PnL counter gives a running approximation. For full metrics over a ~4.7-month sample (87 closed trades, 90.80% win rate, 1.62% max drawdown, profit factor 4.183, +3.38% net return), use the companion strategy version on identical parameters.
🔷 How to Use It:
🔸 Add the indicator to a 5m POL / USDT chart.
🔸 Review the RSI trigger level, the averaging-order count/deviation/size, the Take Profit, Trailing, and Stop Loss percentages. Defaults mirror the source DCA Bot configuration.
🔸 Set Base Order Size and AO sizes to match your bot's configuration (the avg-entry display becomes meaningful when virtual sizing matches real sizing).
🔸 In the DCA Bot Webhook group, paste the Bot ID, Email Token, and Pair (QUOTE_BASE format, e.g., USDT_POL).
🔸 Create an alert on the indicator with "Any alert() function call". Paste the DCA Bot's webhook URL into the alert's Webhook field. The indicator will emit JSON payloads for entry, each averaging order, and the TP/SL exit — formatted for direct DCA Bot consumption.
🔷 INDICATOR SETTINGS
Base Order Size (USDT): Virtual order size for the avg-entry / open-PnL computation.
Averaging Orders per Trade: Number of safety orders (default 3).
First AO Size (USDT): Virtual size of each averaging order (uniform by default).
Deviation to First AO (%) / Deviation Step Multiplier: Spacing of the AO ladder above base entry. Defaults to uniform +1% steps.
Order Size Multiplier: Per-rung size scaling (1.0 = uniform).
RSI Timeframe / Length / Crossing Down Level: The RSI(9) crossing-down trigger (default 5m).
Take Profit (%) / Trailing (%): TP distance below average entry and the trailing retrace that closes the position.
Stop Loss (%): Hard stop above average entry.
Active Window: Optional date filter — when ON, the indicator only fires signals between From and To dates.
DCA Bot Webhook: Bot ID, Email Token, and Pair fields injected into every alert payload.
Visualization: Toggle DCA Ladder, Avg / TP / SL plot lines, fill labels, signal triangles, status table.
Brand Watermark: Configurable text, position, size, and transparency.
👨🏻💻💭 We hope this tool helps enhance your trading. Your feedback is invaluable, so feel free to share any suggestions for improvements or new features you'd like to see implemented.
__
The information and publications within the 3Commas PulseWire account are not meant to be and do not constitute financial, investment, trading, or other types of advice or recommendations supplied or endorsed by 3Commas and any of the parties acting on behalf of 3Commas, including its employees, contractors, ambassadors, etc. Indicator
[3Commas] POL RSI Reversal DCA - Short Strategy POL RSI Reversal DCA - Short Strategy
🔷 What it does:
This is a short-only DCA strategy that fades overbought momentum on POL / USDT. A short deal opens when the 5-minute RSI(9) crosses down through 80 — a momentum-exhaustion signal after a fast push higher. Up to three averaging orders then fill at fixed deviations ABOVE the base entry (+1%, +2%, +3%) with uniform sizing, pulling the average entry up if price keeps rising. Exit is a 1.3% Take Profit from the average entry with a 0.3% trailing retrace, and a hard 8% Stop Loss caps the downside.
- Single base order plus up to three uniform averaging orders on a fixed +1% / +2% / +3% ladder.
- Tight 1.3% Take Profit with a 0.3% trailing lock — captures the mean-reversion snap-back, then trails to squeeze a little extra.
- Hard 8% Stop Loss closes the trade if the short keeps running against the position — a real, bounded per-trade risk.
- Every entry, averaging order, and exit emits a webhook-ready JSON alert payload for direct DCA Bot consumption.
🔷 Who is it for:
- Intraday traders fading overbought spikes on POL on lower timeframes.
- Bot operators who want to drive a DCA Bot short deal from PulseWire alerts with per-event JSON payloads.
- Traders who want a mechanical short with a defined stop, modest averaging, and a quick profit target rather than an open-ended hold.
- Portfolio operators looking for a high-win-rate, short-side contributor with bounded risk.
🔷 How does it work:
Entry Trigger: A 5-minute RSI(9) is sampled via request.security with lookahead disabled (no repaint). The base short opens when that RSI crosses DOWN through 80 — i.e., the prior 5m close was ≥ 80 and the current is below it, marking the moment overbought momentum rolls over.
Base Order: Sized at 500 USDT default (5% of 10k capital), placed as a Limit order at the signal bar's close (Market toggle available).
Averaging Orders (Uniform DCA Ladder): After the base fill, the strategy monitors price deviation above the base entry. Each averaging order has a fixed deviation — +1%, +2%, +3% — with uniform sizing (250 USDT each, half the base). If price rises against the short, each rung adds size and raises the average entry, so a smaller reversal is needed to reach Take Profit.
Exit (TP + Trailing): A 1.3% Take Profit below the running average entry arms a trailing exit. Once price trades through the TP level, the strategy tracks the in-favor low and closes when price retraces 0.3% off that low — locking the move while letting it extend.
Stop Loss: A hard 8% Stop Loss above the average entry. If price runs against the short past that level, the position closes at market. This is the strategy's defined, bounded per-trade risk.
🔷 Why it's unique:
- Momentum-Exhaustion Trigger: Rather than shorting any overbought reading, the deal opens specifically on the RSI crossing DOWN through 80 — the rollover moment — which filters out trades that fire while momentum is still climbing.
- Defined-Risk DCA: Most martingale DCA shorts run without a stop. This one keeps a modest 3-rung uniform ladder AND an 8% hard stop, so the worst-case loss per deal is bounded and known in advance.
- Trailing Take Profit: The 1.3% target arms a 0.3% trailing exit rather than a fixed limit — capturing the reversion snap and then riding any follow-through.
- DCA Bot Integration: Every event (base, AO 1–3, exit) emits a fully-formed JSON alert payload. Connect one alert to a DCA Bot's webhook URL and the strategy drives the bot end-to-end without any glue layer.
🔷 Considerations Before Using the Strategy:
Sample Size: The backtest produced 87 closed trades — just below the ~100-trade floor commonly used for statistical confidence. The 90.80% win rate and 4.183 profit factor reflect favorable conditions over the test window; treat them as indicative rather than a forward-performance guarantee. Extend the window or run across multiple assets to build a larger sample.
Lower-Timeframe Sensitivity: Tested on a 5-minute chart with a 5-minute RSI trigger. Lower timeframes generate more signals but are more sensitive to noise and fees. Confirm the trade frequency and fee drag fit your execution venue before deploying.
Stop Loss Discipline: The 8% Stop Loss is the defining risk control. With the base plus three averaging orders, maximum deployed capital is ~1,250 USDT (12.5% of default equity); an 8% stop on that position bounds the worst-case loss to roughly 1% of equity. Keep the stop enabled — removing it converts this into an unbounded martingale short.
Trend Risk: Fading overbought conditions works best in ranges and choppy regimes. In a strong, sustained uptrend the short can hit the 8% stop repeatedly. The RSI-crossing-down trigger reduces but does not eliminate this; pair with regime awareness.
Commission Calibration: The default 0.06% commission is calibrated for Bybit perpetual taker conditions. Match it to your exchange's actual fees — on a high-frequency lower-timeframe strategy, fee mismatch materially shifts results.
🔷 STRATEGY PROPERTIES
Symbol: BYBIT:POLUSDT.P (Perpetual) — portable to any POL / USDT pair.
Timeframe: 5M chart (5M RSI trigger).
Test Period: March 26, 2026 — June 18, 2026 (~2.7 months).
Initial Capital: 10,000 USDT.
Order Size: 500 USDT base (5%) + 3 averaging orders of 250 USDT each (uniform).
Max Capital Deployed: ~1,250 USDT per trade (~12.5% of equity).
Commission: 0.06% per trade.
Slippage: 3 ticks.
Margin for Short Positions: 100% (1× leverage, Isolated in source config).
Indicator Settings: Default Configuration.
Base Order: 500 USDT, Limit by default (Market toggle available).
Entry Trigger: 5m RSI(9) Crossing Down 80.
Averaging Orders: 3 with fixed deviations +1% / +2% / +3% above base entry; uniform 250 USDT sizing.
Take Profit: 1.3% below average entry, with 0.3% trailing.
Stop Loss: 8% above average entry (hard close).
Strategy: Short Only.
🔷 STRATEGY RESULTS
⚠️ Remember, past results do not guarantee future performance.
Net Profit: +337.89 USDT (+3.38%)
Max Equity Drawdown: 164.93 USDT (1.62%)
Total Closed Trades: 87
Percent Profitable: 90.80% (79 / 87)
Profit Factor: 4.183
🔷 How to Use It:
🔸 Adjust Settings: Open the strategy inputs and review the Base Order Size, the averaging-order count/deviation/size, the RSI trigger level, the Take Profit and Trailing percentages, and the Stop Loss. Defaults mirror the source DCA Bot configuration — recalibrate per asset and timeframe.
🔸 Results Review: This configuration produced 87 closed trades over the test window — just below the ~100-trade floor for statistical relevance. Extend the window or test across multiple assets to firm up confidence, and confirm the win rate, drawdown, and trade frequency fit your risk tolerance before deploying capital.
🔸 Create alerts to trigger the DCA Bot: Add one alert on the strategy using "Any alert() function call". Paste the DCA Bot's webhook URL into the alert's Webhook field, and fill the Bot ID, Email Token, and Pair inputs on the script. The strategy will emit JSON payloads for entry, each averaging order, and exit — formatted for direct DCA Bot consumption.
🔷 INDICATOR SETTINGS
Base Order Size (USDT): USDT amount opened on the initial short.
Use LIMIT for Base: Toggle between Limit (default) and Market entry.
Averaging Orders per Trade: Number of safety orders (default 3).
First AO Size (USDT): Size of each averaging order (uniform by default).
Deviation to First AO (%) / Deviation Step Multiplier: Spacing of the AO ladder above base entry. Defaults to uniform +1% steps.
Order Size Multiplier: Per-rung size scaling (1.0 = uniform).
RSI Timeframe / Length / Crossing Down Level: The 5m RSI(9) crossing-down trigger for the base short.
Take Profit (%) / Trailing (%): TP distance below average entry and the trailing retrace that closes the position.
Stop Loss (%): Hard stop above average entry.
DCA Bot Webhook: Bot ID, Email Token, and Pair fields injected into every alert payload.
Visualization: Toggle DCA Ladder, Avg / TP / SL plot lines, fill labels, status table.
Brand Watermark: Configurable text, position, size, and transparency.
👨🏻💻💭 We hope this tool helps enhance your trading. Your feedback is invaluable, so feel free to share any suggestions for improvements or new features you'd like to see implemented.
__
The information and publications within the 3Commas PulseWire account are not meant to be and do not constitute financial, investment, trading, or other types of advice or recommendations supplied or endorsed by 3Commas and any of the parties acting on behalf of 3Commas, including its employees, contractors, ambassadors, etc. Strategy
Cycle Alignment [Manaslu]Cycle Alignment is the foundational Congruence component of the ET Massif Framework research suite.
1. Description
Manaslu is a dual adaptive band-pass filter (BPF) derived from concepts popularized by John Ehlers. A band-pass filter is a signal-processing technique designed to emphasize oscillations occurring within a selected range of cycle lengths while suppressing both slower trend components and higher-frequency noise. In market data, this allows cyclical behavior to be isolated and observed more clearly, revealing structure that may otherwise be obscured by broader trends or short-term fluctuations.
What distinguishes Manaslu is that it does not focus on a single filtered signal. Instead, it constructs two independent adaptive band-pass filters, each with its own dynamically estimated cycle period. The objective is to evaluate phase congruence, divergence, and synchronization between two inputs (indicators).
Manaslu is not intended to identify dominant market cycles, perform spectral decomposition, or estimate cycle periodicity for forecasting purposes. Its primary role is to study the phase relationship between two adaptive cyclical structures rather than the characteristics of either structure in isolation.
2. Construct
A. Adaptive Period Estimation
For each input (series), an adaptive cycle period is estimated :
Crossovers between the input and its moving average are identified
The time distance between successive crossover events is measured as a half-cycle and doubled to estimate the full cycle length
A user-defined minimum cycle floor is applied to ensure stability
B. Detrending
A two-bar difference operation detrends each source before filtering. This removes the slower trend component and allows the filter to focus on cyclical behavior.
x = 0.5 × (Price − Price )
C. Band-Pass Filter
The adaptive period is applied to a second-order Ehlers-style band-pass filter.
beta = cos(2π / Period)
gamma = 1 / cos(4π × Delta / Period)
alpha = gamma − √(gamma² − 1)
out = 0.5 × (1 − alpha) × (x − x ) + beta × (1 + alpha) × out − alpha × out
Beta — the frequency tuning coefficient that positions the filter around the target cycle period
Gamma — the bandwidth controller that determines the allowed deviation around the core cycle period using Delta
Delta — the user-defined bandwidth spread parameter controlling the tolerance window around the primary period
Alpha — the smoothing and feedback weight derived from Gamma that controls filter decay and stability
D. Normalization
Each band-pass output is normalized independently against its recent peak amplitude. This allows two inputs with different scales, volatility profiles, or magnitudes to be compared directly. The examples shown in this script description uses an oscillator as the primary input and a moving average as the comparator input for the band-pass filter. These inputs are for illustrative purposes only and are not part of the script itself.
3, Rationale
Band-pass filters are applied primarily to extract cyclic behavior and reduce the impact of random noise and fluctuations. By attenuating both very slow and very fast movements, a band-pass filter can produce a cleaner representation of the market's oscillatory structure. In the context of Manaslu, the objective is not to forecast future cycles but to create a consistent framework for comparing indicator on indicator phase congruence.
Potential inputs include moving averages, RSI variants, oscillators, denoised trend indicators, adaptive filters, and other cyclical or transformed data series.
Picture Danny (John Travolta) and Sandy (Olivia Newton-John) on the dance floor in Grease. Each dance to their own beat and rhythm. When both move in rhythm, the performance appears coordinated and confident. When one speeds up, slows down, or turns against the other, the performance becomes less coherent — even though both are still moving. Manaslu attempts to visualize that relationship between two indicators. The focus is on how congruently they move together, not on the individual cycles themselves.
4. Interpretation
A. In-Phase
Both cycles rise and fall together. This suggests broad agreement between the selected inputs. Indicators exhibiting strong phase congruence may warrant greater confidence.
B. Approximately 180° Out of Phase
The cycles move in opposite directions. Both structures remain active but opposing forces are present. This condition may indicate reduced directional efficiency, internal conflict, or a tendency for moves to taper as opposing influences interact.
C. One Stable, One Erratic
One cycle exhibits coherent structure while the other appears unstable or erratic. Users should determine which input carries greater analytical importance — which is closer to price, which is driving decision-making, and whether the erratic structure is background noise or beginning to influence price behavior. Context matters more than visual appearance alone.
D. Both Erratic
Neither cycle displays clear structure. Phase relationships become unreliable. Confidence in the underlying indicators should generally be reduced until more coherent structure emerges. General Caveats
Band-pass filters are sensitive to changing market conditions. Phase relationships can shift rapidly during transitions between trend and range environments. Temporary synchronization does not imply causation, prediction, or future persistence. Manaslu should be viewed as a relationship analysis tool rather than a standalone signal generator.
Like all filters, a band-pass filter represents a mathematical model rather than a direct observation of market behaviour. Its output depends on the selected parameters and may change as market conditions evolve. Consequently, the filtered waveform should be interpreted as a representation of cyclical structure rather than proof of an underlying market cycle.
Default Settings
Bandwidth: 0.025
Minimum cycle length: 40
Primary Input: HL2
Comparator Input: Close
To use another indicator's output as an input, add that indicator to your chart, then in the Settings → Inputs tab select the relevant plot from the input dropdown.
日本語概要 (Japanese Summary)
Manaslu は、ET Massif Framework における Congruence（整合性） 研究コンポーネントです。 独立した2つの適応型サイクル構造を比較し、その位相の同調や乖離、同期状態の観測を目的としています。 なお、本指標は将来のサイクル予測やドミナントサイクルの検出を目的とするものではありません。 移動平均線、RSI、オシレーター、各種フィルターといった異なる指標間の関係性を評価し、2つの構造がどの程度協調して動いているかを観察するための分析ツールです。
中文概要（Chinese Summary）
Manaslu 是 ET Massif Framework 中的 Congruence（整合性） 研究元件。 本指標旨在比較兩個獨立的自適應週期結構，並觀察其相位的一致、不一致以及同步狀態。
須注意的是，本指標並非用於未來週期預測，亦非用於偵測主導週期（Dominant Cycle）。其主要用途在於評估不同指標之間的關聯性，例如：均線、RSI、震盪指標以及各類濾波器等。
它並非針對週期本身進行常規分析，而是一款用以觀察兩個結構之間協調運作程度的分析工具。
Disclaimer:
This script is a research tool for market structure analysis and educational purposes only. It does not constitute financial advice. Trading involves risk. Indicator
Indicator
Indicator
RM Dynamic CPR for ScalpingRM Dynamic CPR for Scalping
Overview
RM Dynamic CPR for Scalping is a dynamic Central Pivot Range (CPR) indicator designed for intraday traders and scalpers. Unlike traditional daily CPR indicators, this script calculates CPR levels using the previous candle of a user-selected higher timeframe (default: 25 minutes), making it highly adaptive to changing market conditions.
The indicator automatically plots CPR levels along with multiple support and resistance zones, helping traders identify potential breakout, breakdown, reversal, and target areas throughout the trading session.
Features
Dynamic CPR Calculation
* Calculates CPR using the previous higher timeframe candle.
* User-selectable CPR timeframe (default: 25 minutes).
* Automatically updates CPR levels when a new timeframe period begins.
CPR Components
* **TC (Top Central)**
* **BC (Bottom Central)**
* **Pivot Point**
Support & Resistance Levels
* R1 / S1
* R2 / S2
* Optional R3 / S3
Visual Enhancements
* CPR zone highlighted using a shaded area between TC and BC.
* Optional line extension for better chart visibility.
* Clean and lightweight design suitable for scalping and intraday trading.
How to Use
Bullish Setup
* Price sustains above the CPR zone.
* CPR acts as support.
* Breakout above R1 may indicate bullish continuation.
* R2 and R3 can be used as potential targets.
Bearish Setup
* Price sustains below the CPR zone.
* CPR acts as resistance.
* Breakdown below S1 may indicate bearish continuation.
* S2 and S3 can be used as potential downside targets.
Range-Bound Markets
* CPR can act as a mean-reversion zone.
* Traders may look for reversals near support and resistance levels.
Best Use Cases
* Index Scalping
* Intraday Trading
* Futures Trading
* Options Trading
* Breakout and Breakdown Strategies
* CPR-Based Confluence Trading
Customization
Users can:
* Change the CPR timeframe.
* Enable or disable CPR levels.
* Show or hide Pivot, R1/S1, R2/S2, and R3/S3 levels.
* Extend plotted levels across the chart.
Disclaimer
This indicator is intended for educational and informational purposes only. It does not provide financial advice. Always use proper risk management and combine CPR levels with price action, volume analysis, and market structure before making trading decisions.
Indicator
Hurst Cycle Alignment Board█ OVERVIEW
The Hurst Cycle Alignment Board fits three fixed cycles from J.M. Hurst's nominal model, the 40-week, 20-week and 10-week cycles, to the chart's price series and shows them as three direction-colored waveforms in a separate pane, shading the background when all three move the same way. It is a regime and timing view built on the premise that price contains a small set of harmonically related cycles whose turning points tend to cluster when the cycles align.
█ HISTORY / BACKGROUND
The cycle lengths come from the nominal model described by J.M. Hurst in "The Profit Magic of Stock Transaction Timing" (1970) and his later cyclic work. Hurst proposed that price action across markets is dominated by a recurring set of cycles related to one another by small integer ratios, most often 2 to 1. The three lengths used here are consecutive harmonics of that ladder: the 40-week cycle (average wavelength about 38.97 weeks) divides into two 20-week cycles (about 19.48 weeks), which divide into two 10-week cycles, the latter also called the 80-day cycle (about 9.74 weeks, near 68.2 calendar days).
Three of Hurst's stated principles motivate viewing them together rather than singly: harmonicity (cycles relate by simple ratios), synchronicity (cycles tend to trough together) and proportionality (longer cycles carry larger amplitude). The fitting method applied to those fixed lengths, a single-frequency least-squares projection, is a standard signal-processing technique. The script does not search for or discover cycle lengths; the three periods are fixed inputs.
█ HOW IT WORKS
For each of the three cycles the script performs the same steps, all on the chart's own series:
• Period in bars. Each length is entered in calendar weeks and converted to a bar count at runtime. On a daily chart the count is weeks multiplied by the Market days per week setting; on a weekly chart it is the number of weeks; on a monthly chart it is weeks divided by 4.345. Results are rounded and floored at a small minimum.
• Detrend. The script takes the natural log of the source and subtracts a simple moving average of that log series. The averaging length is the long-cycle bar count multiplied by the Detrend length factor, removing slow trend before the fit.
• Single-frequency fit. With angular frequency w = 2*pi / period and t = bar_index, the script computes two rolling correlations over a trailing window of length L (the cycle period multiplied by the Fit window factor): a = 2/L * sum(detrended * cos(w*t)) and b = 2/L * sum(detrended * sin(w*t)). These are the least-squares coefficients of one sinusoid at that frequency, equivalent to a single bin of a discrete Fourier transform (a Goertzel-style evaluation). The fitted cycle value at any bar is a*cos(w*t) + b*sin(w*t), and its amplitude is A = sqrt(a^2 + b^2).
• Significance. Each cycle's significance is the share of windowed variance it explains: 0.5*(a^2 + b^2) divided by the variance of the detrended series over the same window, clamped to the range 0 to 1.
• Normalization and stacking. Each fitted cycle is divided by its own amplitude to a unit-amplitude waveform and placed in its own horizontal band, separated by the Band spacing value, so the three appear stacked in one pane.
• Direction and alignment. A cycle is treated as rising when its current fitted value is greater than or equal to the previous bar's value. When all three rise the background shades in the rising color; when all three fall it shades in the falling color; otherwise it is unshaded. The first bar of each all-rising or all-falling stretch is marked with a triangle on the main price chart.
A composite waveform, labeled "push", is the significance-weighted (or equal-weighted) average of the three normalized cycles and can optionally be drawn in a fourth band. A forward projection extends each cycle, and the composite, to the right of the last bar by evaluating the same a*cos(w*t) + b*sin(w*t) expression at future bar indices using the last bar's coefficients.
█ HOW TO USE
Recommended timeframe: daily, weekly or monthly. The cycle lengths are multi-week, so they are meaningful only on these resolutions; on intraday the output is suppressed and an on-chart note is shown. The daily chart is the primary design target, because the periods, expressed in trading days through the Market days per week setting, map to one bar per day.
Reading the output:
• The three waveforms, top to bottom, are the 40-week, 20-week and 10-week cycles, each colored by direction.
• Background shading marks stretches where all three cycles move the same way. Unshaded stretches are mixed.
• Triangles on the price chart mark the bar where a fully aligned stretch begins, up-triangles for all rising and down-triangles for all falling.
• The table at the top right lists each cycle's period in bars and weeks, its significance value and its current direction, plus a today row showing the overall state: ALL UP, ALL DOWN or MIXED.
• The forward projection to the right of the last bar is the deterministic continuation of each fitted cycle. It is a model output, not a price target.
Set Market days per week to match the instrument: 5 for stocks, indices, futures and forex; 7 for markets that trade every day, such as crypto, so a given calendar cycle maps to the correct number of daily bars.
█ SETTINGS
Cycles (calendar weeks)
• Long cycle (40-week) . Long cycle length in calendar weeks. Default 38.97.
• Mid cycle (20-week) . Mid cycle length in calendar weeks. Default 19.48.
• Short cycle (10-week) . Short cycle length in calendar weeks. Default 9.74.
Instrument / timeframe
• Market days per week . Trading days per week, used to convert weeks to bars on daily charts. Default 5.
Fit
• Source . The series the cycles are fitted to. Default close.
• Fit window (x period) . Length of the trailing least-squares window, as a multiple of each cycle's period. Default 3.0.
• Detrend length (x long period) . Length of the trend-removal moving average, as a multiple of the long-cycle bar count. Must exceed 1. Default 1.5.
Display
• Rising . Color for a rising cycle. Default teal.
• Falling . Color for a falling cycle. Default red.
• Band spacing . Vertical distance between the stacked cycle bands. Default 2.4.
• Project cycles forward . Draws the forward projection. Default on.
• Projection length (bars) . Number of bars projected forward, limited to 400. Default 250.
• Projection step . Draws one projected segment every N bars to limit object count. Default 3.
• Show composite (push) band . Draws the composite waveform in a fourth band. Default off.
• Weight composite by fit significance . When on, the composite weights each cycle by its significance; when off, the three are equally weighted. Default on.
█ WHAT MAKES IT ORIGINAL
The script is a self-contained implementation that combines three elements in one tool. First, it fixes the three cycle lengths to Hurst's nominal harmonics rather than searching for dominant periods. Second, it determines each cycle's phase and amplitude automatically by a single-frequency least-squares fit (a one-bin DFT) to detrended log price, recomputed every bar, instead of anchoring cycles to a manually chosen pivot or to a future line of demarcation. Third, it reduces the three cycles to a single regime read by shading only when all three agree in direction and by marking the onset of each aligned stretch on the price chart.
Because the chosen lengths are true 2-to-1 harmonics, the all-aligned condition corresponds to the synchronized turning that Hurst's model expects, rather than a coincidental phase overlap of unrelated periods. The lengths are entered in calendar weeks and converted to bars from the chart timeframe and a trading-days-per-week setting, so the same nominal cycles apply consistently across instruments and across daily, weekly and monthly resolutions.
█ NOTES / LIMITATIONS
• Repainting. The fit is recomputed on every bar over a trailing window, so both the historical cycle estimates and the forward projection update as new bars arrive, and a cycle's direction can change on the developing bar. Treat the most recent bars and the projection as provisional until the bar closes. The script uses no request.security calls and no lookahead.
• Timeframe. Only daily, weekly and monthly are supported. On intraday resolutions all output is suppressed and an on-chart note is shown.
• History required. Each cycle needs roughly the detrend length plus the fit window of prior bars before it returns a value. At default settings on a daily chart this is on the order of 900 bars for the long cycle, so on symbols with little history the long cycle may not render until enough bars exist.
• Forward projection bounds. The projection extends a fixed number of bars (default 250, capped at 400). Pine does not draw beyond about 500 bars into the future, so the projection cannot be extended arbitrarily far.
• Object and compute limits. The projection is drawn with line objects, capped at 500 and internally held under 490; the Projection step setting reduces the count by drawing one segment every N bars. The maximum historical reference is set to 1800 bars.
• Instrument setting. There is no symbol-class restriction, but Market days per week must match the instrument (5 for conventional markets, 7 for markets trading every day); otherwise the calendar-to-bar conversion on daily charts will be off.
• Amplitude display. Each cycle is normalized to unit amplitude for the stacked display, so band height does not convey relative cycle strength; the significance column in the table carries that information. Indicator
Previous Candle High Low [JoeyWave]Previous Candle High Low
The previous candle's High and Low for any timeframe — set it once, read it on any chart.
█ WHAT IT DOES
Draws two horizontal levels: the High and the Low of the previous candle on your chosen timeframe (default H4). Same idea as Previous Day High/Low (PDH/PDL), but the period is yours to pick — H1, H4, Daily, Weekly, anything.
These levels are clean liquidity references: the prior candle's extremes are where stops rest and where price often reacts.
█ FEATURES
▮ Any timeframe
Pick the period once (default H4). The label auto-names itself — "Previous H4 High", "Previous D1 Low", etc.
▮ Smart timeframe clamp
View a chart below your chosen timeframe (e.g. M5 chart, H4 setting) and it auto-raises to the chart timeframe instead of breaking — always a valid level, no errors.
▮ Non-repainting
Levels are taken from the last fully closed candle of the chosen timeframe — they don't repaint.
▮ Fully customizable
Line style (solid / dashed / dotted), colors, label on/off, price on/off, and label offset to push the text toward the right edge.
█ SETTINGS
· Timeframe — which period's previous candle to read (default H4)
· Show Previous High / Low — toggle each level
· Line Style / Colors — appearance
· Show Labels / Show Price / Label Offset — label control
█ NOTES
· Works on every market and timeframe
· Choosing a timeframe ≥ chart timeframe gives the truest reading
· Pairs well with market-structure and liquidity-based setups
Built on Pine v6.
Indicator
Bitcoin Power Law Bands | Astral Vision Capito — niente sezione "source code protected" e niente paywall framing, dato che è open source. Ecco la versione corretta:
Bitcoin Power Law Bands | Astral Vision 🌠💠
Bitcoin's price history follows a remarkably consistent power law growth pattern, where the relationship between price and time, when both are expressed logarithmically, forms a structure that has held across more than a decade of market cycles. This indicator plots a full set of power law bands derived from that relationship, anchored to historically observed turning points across Bitcoin's complete price history, and converts the position of price within those bands into a normalized oscillator that makes the current cycle position immediately readable.
The power law model used here is time-segmented: rather than fitting a single static curve to all of Bitcoin's history, the model recalibrates its growth exponent across distinct historical phases, each anchored to a specific cycle low or high date. Each phase boundary is defined by a precise historical timestamp, and the local growth exponent h is interpolated continuously between these anchors using a base-4 progression. This segmented approach captures the documented deceleration in Bitcoin's growth rate as the asset matures, rather than assuming the same growth rate observed in the earliest years continues indefinitely.
The bands are constructed from the standard power law formula price = 10^(p1 + p2 × log10(h)), where h is the time-segmented exponent described above. Around this central curve, four bands are generated using a deviation term that itself decays as a function of h raised to a configurable power, multiplied by fixed standard-deviation-style coefficients (-3, -1.5, +4, +5) to produce the lower extreme, lower moderate, upper moderate, and upper extreme bands respectively. The decay structure means the bands compress proportionally as h grows, reflecting the empirical narrowing of Bitcoin's volatility envelope in log space over time.
The oscillator at the bottom of the indicator translates the absolute price position within these bands into a normalized 0 to 1 scale, where 0 represents the lower extreme band and 1 represents the upper extreme band. This transformation makes it possible to read Bitcoin's position within its long-term growth channel as a single number, comparable across any period in Bitcoin's history regardless of the dramatic difference in absolute price levels between, for example, 2015 and 2025.
The faded projection lines extending into the future use the same model structure carried forward from the most recent anchor, providing a visual reference for where the bands are mathematically projected to sit if the established growth pattern continues, without making any claim about whether price will actually follow that path.
This indicator is open-source. The full calculation, including the exact anchor timestamps, the segmented exponent interpolation, and the band deviation formula, is visible directly in the script for anyone who wants to study or build on the methodology.
Analytical Framework
Type of analysis: long-term structural growth modeling, cycle position assessment
Recommended timeframe: daily or weekly chart, for long-term position trading and cycle analysis exclusively. Not suitable for short-term or intraday use.
Signal type: deterministic power law bands with a normalized 0-1 position oscillator
How to interpret the signals
The candle coloring on the price chart provides the simplest read: when price closes above the upper moderate band, the candles take on the positive color, indicating Bitcoin is trading in the upper portion of its long-term growth channel, a zone that has historically corresponded to mid-to-late cycle conditions. When price closes below the lower moderate band, the candles take on the negative color, indicating Bitcoin is trading in the lower portion of its growth channel, a zone that has historically corresponded to deep value territory following major corrections.
The oscillator provides the same information with more granularity. A reading near 1.0 means price is pressed against the upper extreme of the historical growth channel, a condition that has, in every previous instance across Bitcoin's history, preceded a significant correction. A reading near 0.0 means price is pressed against the lower extreme, a condition that has, in every previous instance, marked one of the best long-term accumulation opportunities available. The two horizontal reference levels on the oscillator mark where the moderate bands sit on the normalized scale, making it easy to see when price transitions from the middle of the channel into either extreme zone.
Because the bands recalibrate their growth exponent at each historical cycle boundary, the position of price within the channel should be interpreted relative to the current cycle's specific band placement rather than assuming the same absolute price level carries the same meaning it did in a previous cycle.
How it differs from existing tools
Most power law indicators on PulseWire fit a single static exponent across the entirety of Bitcoin's history, which forces a tradeoff between fitting the early years accurately and fitting recent years accurately. This indicator instead segments the growth model across historically anchored cycle boundaries, allowing the exponent to adapt as Bitcoin's growth rate has empirically decelerated. The normalized 0-1 oscillator is also a meaningful addition: rather than requiring visual inspection of where price sits between curved logarithmic bands, it converts that position into a single comparable number.
Plots 📊
Four power law bands on the price chart: upper extreme, upper moderate, lower moderate, lower extreme
Faded future projection lines extending the band structure forward
Candle coloring on the price chart reflecting current position relative to the moderate bands
Normalized 0-1 oscillator in the sub-panel with reference levels marking the moderate band positions
Inputs 🎛️
This indicator has no configurable settings beyond color selection; all band parameters are fixed based on historical calibration and visible directly in the open-source code.
Colors 🎨
5 Astral Vision presets + custom override. Default: Futura.
Disclaimer ⭕️
This indicator is for informational and educational purposes only. It does not constitute financial advice. Past performance is not indicative of future results. Always do your own research before making investment decisions. Indicator
Indicator
