Volatility Cone & Analog Path ProjectionVolatility Cone & Analog Path Projection — Forward Price Envelope with Fractal Replay and Terminal Probability Distribution
Overview
Nearly every overlay on PulseWire describes the past: where price has been, where volume traded, where structure broke. This tool points in the other direction. It builds a forward projection zone from the current bar using three independent layers — a realized-volatility cone, a replay of the historically most similar price fractals, and a terminal probability profile that combines both into a distribution of possible outcomes at the projection horizon.
The result is not a forecast. It is a bounded expectation: a visual answer to "given how this instrument has actually been moving, what range is normal over the next N bars, and where has price historically ended up after conditions that looked like this?"
Conceptual Framework
Price uncertainty grows with the square root of time, not linearly. A 24-bar projection is not 24 times as wide as a 1-bar projection — it is roughly 4.9 times as wide. Traders who size targets and stops on a straight-line mental model consistently misjudge what is achievable in a given number of bars.
The cone makes that curvature visible. Its width at each future bar is sigma * sqrt(t), where sigma is the standard deviation of log returns over the volatility window. Three nested bands are drawn, so you can immediately see which targets sit inside the ordinary range, which sit at the statistical edge, and which would require an exceptional move.
The Gaussian model alone, however, is a poor description of real markets: returns have fat tails, and volatility clusters. The analog layer addresses this by ignoring models entirely and asking an empirical question instead — what actually happened, historically, after the market printed this exact shape?
How It Works
Volatility estimation. Log returns are computed bar to bar. Their standard deviation over the volatility window gives the per-bar sigma; their mean gives the drift. Drift can be included or excluded from the cone's centerline.
Cone construction. For each future bar t from 1 to the horizon, the upper and lower bounds are close * exp(drift*t ± k*sigma*sqrt(t)) for each of the three band multipliers. Each band is rendered as a closed polygon with layered transparency, producing depth from the centerline outward.
Fingerprint extraction. The most recent N bars of log returns are z-scored — mean removed, divided by their own standard deviation. This makes the pattern scale-invariant: the same shape is recognised whether it happened during a quiet range or a volatile expansion, and at any price level.
Historical scan. Every candidate window inside the scan depth is z-scored the same way and compared to the current fingerprint by summed squared difference. Lower distance means a closer shape match. Candidates that overlap an already-selected match without improving on it are rejected, so the top results are not five copies of the same event shifted by one bar.
Forward replay. For each of the top matches, the bars that followed it are converted into a relative path and re-anchored to the current close. The path each analog is drawing forward is exactly the move that occurred after that historical fingerprint — nothing is fitted or optimised. Paths ending above the current price are drawn bullish, below bearish, and a thick median line traces the bar-by-bar median across all analogs.
Terminal probability profile. At the projection horizon a horizontal distribution is built across the cone's full range. Each row's density blends the Gaussian probability implied by the volatility model with an empirical kernel centred on each analog's endpoint. The Model Weight input controls that mix: 1.0 is purely theoretical, 0.0 is purely historical, and the default sits between them. The widest row — the mode of the blended distribution — is marked as the most probable zone.
Interpretation
Cone bands define what is statistically ordinary. A target beyond the outer band within the horizon is not impossible, it is simply rare — treat it accordingly when planning holding time.
Cone width itself is information. A narrow cone means compressed volatility, which historically resolves into expansion. A wide cone means the market is already moving; chasing inside it carries a worse risk profile.
Analog dispersion matters more than analog direction. Five paths that fan out in all directions means the current shape carried no historical edge. Five paths clustering in one direction is the meaningful configuration.
Best Match Quality in the panel scores how closely the nearest historical fingerprint resembles the present one. Below roughly 60%, treat the analog layer as noise and rely on the cone alone.
The most probable zone is where the blended distribution peaks. It is a magnet-style reference, not a target — the distribution is wide by construction.
Volatility Regime compares short-window volatility to the full window. Expanding means the cone is likely to understate near-term movement; contracting means the opposite.
Settings
Setting Effect
Projection Horizon Bars projected forward. Also the endpoint of the profile
Volatility Window Sample size for sigma and drift. Longer = smoother, slower to adapt
Include Drift Tilts the cone with the window's mean return
Inner / Mid / Outer Band Sigma multipliers for the three layers
Fingerprint Length Bars compared for similarity. Shorter = more matches, less specific
Scan Depth How far back to search for analogs
Number of Analogs How many historical paths to replay
Profile Rows / Width Resolution and horizontal size of the terminal distribution
Model Weight Gaussian versus empirical blend in the distribution
Redraw on Bar Close Only Recommended on. The scan is heavy; this runs it once per bar
Limitations — read this
This is not a prediction and must not be traded as one. The cone describes a statistical range under an assumption of stable volatility. Real volatility is not stable, and returns have fatter tails than the Gaussian model implies, so moves outside the outer band occur more often than the model suggests.
Analog matching is weak evidence. A few dozen bars of shape similarity is a small sample; markets are non-stationary and a pattern that resolved one way in the past carries no obligation to repeat. The paths are historical context, not a probability statement about the future.
Nothing repaints, but the whole projection is recomputed each bar. Yesterday's cone is not preserved — the drawing always reflects current data only. It is anchored to the last bar by design.
On low-volume, illiquid, or heavily gapped instruments the return distribution is distorted and both layers degrade.
No entries, no stops, no targets, no signals. This is a context tool for sizing expectations and holding time. Indicator
Auto Trendlines [AFD]Traders!
If this draws fewer lines than the last auto-trendline script you tried, that is not a bug.
Almost every free entrant in this category will connect any two points and call the result a trendline, including points price has already traded straight through. This one will not draw that line at all.
WHAT IT DOES
Two confirmed same-side pivots define a diagonal line - two swing highs for a descending line, two swing lows for an ascending one. Before it is drawn, the pair has to pass four checks, all required:
Same side. Never one high paired with one low.
Progressive. The second pivot has to be lower than the first on a descending line, higher on an ascending one.
No pierce. No bar between the two anchors may have traded through the line.
Still intact now. No bar since the second anchor may have violated it either.
The third check is the one almost everyone in this category skips, and the fourth closes the gap right behind it - a pivot needs time to confirm, so without the fourth check a line could pass the first three and still be dead on arrival, already traded through in the bars since its own anchor. Of every pair that clears all four, the one nearest current price is the one drawn.
It keeps three lines per side by default - one at your Swing Strength setting, and two more at longer multiples of it - so a short, a medium and a long trendline can all be live on the same side at once, each resting on a different swing rather than three readings of the same one.
HOW A LINE LIVES AND DIES
A live line is maintained, not redrawn - its right edge follows price, and its label counts how many bars have touched it within your tolerance. It is retired, dimmed and kept on the chart, never silently deleted, for exactly one of two reasons: price violated it, or its anchor aged past your Bars to Apply setting. A retired line's colour, width and style are yours to set - the defaults reproduce a plain grey dotted line, but a violated line and an aged-out line both use the same styling, because both are "no longer live" and neither claims anything about what happens next.
When a side has nothing to show, an optional note names the refusal directly instead of leaving a blank chart that reads as broken - something like "No valid ascending line - recent pivot pairs failed the validity rule." It disappears the moment a line forms on that side.
THE TWO ALERTS
One alert per side, on one event: a line was violated and retired, on the bar that just closed. That is the whole alert surface.
It does not fire on a developing bar - only once a bar closes.
It does not fire when a line is retired for age. An aged line was not violated, and an alert saying it was would be a false statement about your chart.
It does not tell you what to do next. It names the event and points at the settings that produced it.
There is no alert for a line forming, for a touch, or for price approaching a line.
SETTINGS WORTH KNOWING FIRST
Swing Strength sets how many bars either side of a pivot must confirm it - higher means steadier, later pivots; lower means more of them, sooner and noisier. Pivots Searched sets how many recent pivots each length keeps in its pool to test pairs from. Pierce Tolerance and Touch Tolerance are both a multiple of ATR: Pierce is how far price may travel through a line before it counts as pierced or violated, and Touch is the separate band used only for counting touches. Bars to Apply bounds how old a line's anchor may get before it ages out - 0 means no limit.
Minimum Touches is worth reading twice, because it does not do what it sounds like. Requiring touches before a line can be drawn does not find a better line - it defers the same line's appearance into a later, shorter-lived part of its own life, since touches accrue before the line is drawn, not after. What it actually buys is recency: the lines that survive it are the ones price is currently working on.
Label position offers "Right of line" (default, floats along the line's own slope) or "Below, centered" (sits directly under the line's tip). Either way the label is a plain box with no pointer.
WHAT IT WILL NOT DO
It is not a signal tool. It does not grade a line's strength, does not rank one line against another, and does not name a target, a breakout, or a bounce - each of those is a claim about the bar after the one that just closed, and this script has no view on that. A touch count is a count of what already happened, shown with the tolerance that produced it, nothing more.
WHAT IS DISCLOSED RATHER THAN HIDDEN
A line appears late by design - its anchors are confirmed pivots, so a line shows up Swing Strength bars after the bar that anchors it. That lag is the price of not drawing lines that vanish a bar later.
Whether this script repaints has not been observed on a replay and is not claimed here either way. Its behaviour on a logarithmic price scale is likewise unobserved and unclaimed.
Zero request.*() calls of any kind - every calculation reads the chart's own series.
Open source under the Mozilla Public License 2.0. Indicator
Indicator
Reactive Trail System [WillyAlgoTrader]📊 Reactive Trail System (RTS) is an overlay trend-following indicator that combines a momentum-adaptive trailing stop, a dual volatility engine, a 0–100 signal quality score, and a complete trade-management layer (Entry / SL / TP1–TP3 / break-even) — all tracked live on a sectioned dashboard with win-rate statistics.
The core insight: a trailing stop should not have a fixed width. When momentum is strong, price moves cleanly and the trail can hug price to lock in profit. When momentum fades, price gets noisy and the trail must widen to survive the chop. RTS measures momentum every bar and reshapes the trail width automatically — up to 40% tighter in strong moves — so one setting adapts to changing conditions instead of being permanently too tight or too loose.
If you are new to trailing stops: think of the trail as a colored line that follows price from below in an uptrend (green) and from above in a downtrend (red). As long as price stays on the right side of the line, the trend is alive. When price closes through the line, the trend flips — and RTS turns that flip into a fully managed trade idea with a stop-loss and three targets drawn on the chart for you.
Works on all markets (crypto, forex, stocks, indices, commodities) and all timeframes.
🧩 WHY THESE COMPONENTS WORK TOGETHER
A classic supertrend-style trail has three chronic problems. First, its width is fixed — the same multiplier that protects you in chop gives back too much profit in a strong trend. Second, a raw trail flip says nothing about signal quality — a flip in dead, low-volume conditions looks identical to a flip with real participation. Third, a flip is not a trade — you still have to decide where the stop goes, where the targets go, and when to move to break-even.
RTS solves all three with one integrated pipeline:
Baseline MA (6 engines) → Dual volatility measure (ATR + StDev) → RSI momentum engine → Adaptive trail width → Ratcheting trail state machine → HTF bias + volume filters → 0–100 signal score → Wick-anchored SL + TP1/TP2/TP3 → Break-even automation → Trade outcome statistics
The baseline MA defines the anchor the trail hangs from. The volatility engine defines the raw distance. The RSI momentum engine then compresses that distance when momentum is strong — this is what makes the trail "reactive" rather than static. The ratcheting state machine guarantees the trail only ever tightens in the trade's favor (it never backs away from price). The HTF and volume filters decide whether a flip is allowed to become a trade. The scoring engine grades every entry so you can tell an A-setup from a C-setup at a glance. The risk engine converts the signal into concrete levels anchored to real market structure (the signal bar's wick), and the trade engine tracks every touch, break-even move, stop-out and reversal — feeding honest statistics back to the dashboard.
Remove any link and the chain breaks: without momentum adaptation the trail is just another supertrend; without filters every flip fires; without the wick-anchored stop the levels ignore structure; without outcome tracking you never learn how the system actually behaves on your market.
🔍 WHAT MAKES IT ORIGINAL
1️⃣ Momentum-adaptive trail width — the trail breathes with the market.
Instead of a fixed multiplier, RTS computes a momentum distance from the smoothed RSI and uses it to compress the trail:
— momDist = min(|RSI_smoothed − 50| / 50, 1.0) — 0 means dead-center momentum, 1 means extreme
— effectiveMultiplier = TrailMultiplier × (1 − Adaptivity × momDist × 0.4)
— trailOffset = volatility × effectiveMultiplier
With default Trail Multiplier 2.0 and Adaptivity 1.0, the trail runs at full width in neutral conditions and tightens by up to 40% when RSI pushes toward extremes. Set Adaptivity to 0 and you get a classic fixed-width trail; the default 1.0 gives maximum adaptation. RSI length 13 with EMA smoothing 3 keeps the width changes calm instead of jittery.
Why this matters: strong momentum = clean price movement = you can afford a tight trail that protects open profit. Weak momentum = noise = the trail widens automatically so you don't get shaken out.
2️⃣ Dual volatility engine — ATR, StDev, or a stabilized Hybrid.
Trail distance can be measured three ways (Volatility Length default 13):
— ATR: classic bar-range volatility
— StDev: close-to-close dispersion
— Hybrid (default): (ATR + StDev) / 2
ATR reacts to wicks and gaps; StDev reacts to closing dispersion. Averaging them dampens the weakness of each — a single wild wick inflates ATR but barely moves StDev, so the Hybrid stays stable where a pure-ATR trail would suddenly balloon.
3️⃣ Six baseline engines including KAMA and T3 — with a volume-safety fallback.
The trail anchors to a baseline MA selectable from HMA, ALMA (default, length 21), KAMA, T3, VWMA and EMA. KAMA and T3 are computed from their full formulas internally (Kaufman efficiency-ratio smoothing constant sc = (ER × (fast − slow) + slow)², and Tillson's six-stage EMA cascade with a = 0.7). If you pick VWMA on an instrument whose data feed reports no volume (common on some forex feeds), RTS silently falls back to EMA instead of plotting garbage.
4️⃣ Ratcheting trail state machine — the stop never retreats.
In a bull regime the trail is trail = max(previous trail, baseline − offset): it can only rise. In a bear regime it can only fall. A flip requires a full bar close beyond the trail — intrabar wicks through the line do not flip the trend. This one-way ratchet is what makes the line usable as an actual trailing stop rather than a wavy band.
5️⃣ Non-repainting HTF bias filter.
Optional filter: longs only when the higher timeframe (default 240 = 4H) closes above its 50 EMA, shorts only below. The HTF request uses the last closed HTF bar (index with lookahead), so the bias never changes retroactively — what you see in a live chart is what a backtest would have seen.
6️⃣ Signal quality score 0–100 — every entry is graded, not just fired.
Each entry gets a transparent confluence score:
— Momentum component (0–40): min(momDist / 0.6, 1) × 40
— Volume component (0–30): participation vs the 20-bar volume SMA, clamped; fixed 15 when the feed has no volume
— HTF alignment (10 or 30): 30 when the higher timeframe agrees with the trade direction, 10 when it doesn't
The score is shown in the BUY/SELL label tooltip, in the dashboard "Last signal" row, and in every entry alert. A 90-score long (strong momentum, heavy volume, HTF agrees) and a 45-score long are both valid flips — but you instantly know which one deserves full size.
7️⃣ Wick-anchored stop-loss — structure-aware risk, not a blind ATR offset.
Default SL mode anchors the stop to the signal bar's actual wick:
— Long SL = min(low − 0.25 × ATR, close − 0.5 × ATR)
— Short SL = max(high + 0.25 × ATR, close + 0.5 × ATR)
The 0.25 × ATR buffer sits the stop just beyond the wick (where stop-hunts reach), and the 0.5 × ATR minimum distance prevents absurdly tight stops on small-bodied signal bars. A classic fixed ATR mode (SL = entry ± multiplier × ATR, ATR length 14) is available too. Targets are pure R-multiples of the actual risk: TP = entry ± risk × multiplier.
Four one-click risk presets: Conservative (SL 2.5×ATR, TP 1R/2R/4R), Balanced (default: 1.5×ATR, 1R/2R/3R), Aggressive (1.0×ATR, 1.5R/2.5R/4R), Scalping (0.8×ATR, 0.8R/1.5R/2R), plus a fully manual Custom preset with input validation (TP1 < TP2 < TP3 enforced).
8️⃣ Full trade lifecycle engine with honest intrabar rules.
RTS doesn't just draw levels — it tracks the trade like a journal:
— Hits are checked only on confirmed bars, and never on the entry bar itself (entry-bar guard)
— TP-priority model: if a bar touches both a TP and the SL, the TP touch registers first (this optimistic assumption is disclosed right in the dashboard tooltip)
— Break-even automation: once TP1 is touched, the stop moves to entry; a BE moved this bar cannot stop you out on the same bar
— Opposite confirmed signal reverses the position (closes the old trade, opens the new one)
— Win definition is fixed and transparent: a trade counts as a WIN once TP1 has been touched (TP3 close, BE stop-out after TP1, or reversal after TP1); closed before TP1 = loss
9️⃣ Persistent trade visualization.
Entry (subtle dotted), SL (solid, prominent) and TP1/TP2/TP3 (dashed) lines extend with the live trade. When a TP is touched, its line turns solid teal with a ✓ on the label. When break-even activates, the original SL line dims to a record and the entry label is annotated "→ SL (BE)". After the trade closes, the drawing persists as a record until the next entry replaces it — you can scroll back and see exactly how each trade resolved.
🔟 Dashboard 2.0 with period-filtered statistics.
A sectioned panel (Market / Trade / Stats — each toggleable, position and font size configurable):
— Market: trend direction, trend age in bars, HTF bias, smoothed RSI, last signal with score and bars-ago
— Trade: entry, SL (with "BE @" marker), TP1–TP3 with ✓ checkmarks, R:R at TP1, SL distance in % — collapses to one row when flat
— Stats: closed trades, wins, losses, win rate with a ▰▱ gauge, and a "Form" strip of the last 10 results
The win-rate window is selectable: last 24 Hours, last 30 Days, or All-Time — computed from timestamped trade closures kept in a rolling 31-day buffer. Statistics reset on chart reload, and this is disclosed directly in the dashboard tooltips.
📖 HOW IT WORKS — CALCULATION FLOW
Step 1 — Baseline: the selected MA engine (ALMA 21 by default) is computed as the trail anchor.
Step 2 — Volatility: ATR and StDev over 13 bars are combined per the selected engine into one volatility measure.
Step 3 — Momentum: RSI(13) is EMA-smoothed(3); its distance from 50 (normalized 0–1) compresses the trail multiplier by up to 40%.
Step 4 — Trail update: the ratcheting state machine raises the trail in bull regimes / lowers it in bear regimes; a confirmed close through the trail flips the regime.
Step 5 — Filtering: the flip becomes an entry signal only if it passes the optional HTF bias and volume-confirmation filters, on a confirmed bar, after the warm-up period.
Step 6 — Scoring: the entry is graded 0–100 from momentum, volume participation and HTF alignment.
Step 7 — Risk placement: SL is anchored to the signal bar's wick (or fixed ATR), TP1–TP3 are projected as R-multiples of the actual risk per the active preset.
Step 8 — Trade tracking: every confirmed bar is checked for TP touches, break-even activation, stop-out or reversal; outcomes update the win/loss statistics and the Form strip.
📖 HOW TO USE
🎯 Quick start:
1. Add the indicator to your chart. Defaults (ALMA 21, Hybrid volatility, Balanced preset) are ready to use.
2. Wait for a ▲ BUY or ▼ SELL label — hover it to see the score, RSI, SL and TP1.
3. Check the dashboard: score of the last signal, HTF bias, and current R:R.
4. Prefer high-score signals (70+) where the HTF bias agrees with the trade direction.
5. Manage by the drawn levels: partial at TP1 (stop moves to break-even automatically), remainder toward TP2/TP3 or until the trail flips.
👁️ Reading the chart:
— 🟢 Green trail line below price = bull regime; it can only rise
— 🔴 Red trail line above price = bear regime; it can only fall
— ▲ BUY / ▼ SELL labels = filtered, confirmed entries (tooltip shows score and levels)
— Dotted line = entry reference · solid red = stop-loss · dashed green = TP1/TP2/TP3
— Teal solid TP line with ✓ = target reached · dimmed SL + "→ SL (BE)" = stop moved to entry
— Optional: soft trend fill between trail and baseline, and regime-colored candles
📊 Dashboard fields:
— Trend / Age: current regime and bars since the last flip
— HTF Bias: higher-timeframe direction (Off when the filter is disabled)
— RSI: the smoothed momentum value driving trail width
— Last signal: direction · score (bars ago)
— Entry / SL / TP1–TP3 / R:R / SL Dist: full live trade card
— Trades / Wins / Losses / Win rate: statistics for the selected period (24H / 30D / All-Time)
— Form: last 10 results, ▰ = win, ▱ = loss, newest on the right
🔧 Tuning guide:
— Too many flips / whipsaws: raise Trail Multiplier toward 2.5–3.0, raise Baseline Length toward 34–55, or enable the HTF Bias Filter
— Exits feel too late: lower Trail Multiplier toward 1.8, or keep Adaptivity at 1.0 so strong momentum tightens the trail
— Trail width feels jumpy: lower Momentum Adaptivity to 0.4–0.6 or raise Momentum Smoothing to 5–8
— Too few signals: disable the volume filter, or shorten Baseline Length toward 13–21
— Stops too tight on your market: switch the preset to Conservative, or use ATR mode with a higher SL multiplier
— Scalping lower timeframes: Scalping preset + Volatility Length 10 + consider HMA baseline
⚙️ KEY SETTINGS
⚙️ Main:
— Baseline MA Type (default ALMA): trail anchor engine — HMA / ALMA / KAMA / T3 / VWMA / EMA
— Baseline Length (default 21): higher = smoother, fewer flips
— Momentum (RSI) Length (default 13) and Smoothing (default 3): the adaptive-width driver
— Volatility Engine (default Hybrid) and Length (default 13)
— Trail Multiplier (default 2.0): base trail distance in volatility units
— Momentum Adaptivity (default 1.0): 0 = fixed width, 1 = up to 40% tightening
🔍 Filters:
— HTF Bias Filter (default off) + Higher Timeframe (default 240): trade only with the bigger trend
— Volume Confirmation (default off) + Threshold (default 1.2 × SMA20): require real participation; auto-bypassed on no-volume feeds
🛡️ Risk Management:
— Risk Preset (default Balanced): Conservative / Balanced / Aggressive / Scalping / Custom
— SL Mode (default Wick-Anchored): structure-based stop or fixed ATR
— ATR Length (default 14), SL / TP1 / TP2 / TP3 multipliers (Custom preset)
— Break-Even After TP1 (default on)
— SL/TP lines, labels, % distance and per-line styles are all configurable
🎨 Visual:
— Theme Auto / Dark / Light (auto-detects chart background), trail / baseline / fill / labels / candle-coloring toggles, font sizes, bull & bear colors
📊 Dashboard:
— Show/hide the panel and each section, position (4 corners), font size, Win Rate Period (24 Hours / 30 Days / All-Time)
🔔 ALERTS
— 🟢 LONG / 🔴 SHORT — entry with price, SL, TP1–TP3, R:R and score; plain text or JSON webhook payload for bot integration
— 🎯 TP1 HIT / 🎯🎯 TP2 HIT — target touches
— 🏆 TP3 HIT — final target, trade closed
— 🛑 SL HIT / 🛡️ BE STOP-OUT — stop-outs with entry and stop price
— 🛡️ BREAK-EVEN — stop moved to entry after TP1
— 🔄 REVERSAL — opposite signal closed the trade and opened the other direction
— ▲ / ▼ FLIP (optional, informational) — trail flipped but the entry was blocked by filters
All alerts fire once per confirmed bar close. Set up a single alert with "Any alert() function call" and toggle the categories you want in the settings.
⚠️ IMPORTANT NOTES
— 🚫 No repainting. Signals require barstate.isconfirmed; a flip needs a full bar close through the trail; the HTF filter reads only the last closed higher-timeframe bar; all alerts use bar-close frequency. What you see on historical bars is what the live chart produced.
— 📐 Intrabar assumption disclosed. When a single bar touches both a TP and the SL, the TP registers first (optimistic model). This is stated in the dashboard tooltip so the statistics are interpreted correctly.
— 📐 Statistics are session-based. Win/loss counts and the Form strip are computed from the loaded chart history and reset on chart reload. Past performance does not guarantee future results.
— ⚖️ Scope. RTS is a trend-following system — like any trail-based approach it performs best in trending conditions and will flip more often in tight ranges. Use the HTF and volume filters and the score to skip low-quality environments.
— 🛠️ This is an analysis tool, not an automated trading bot. It identifies trend regimes, grades entries, and draws structured risk levels — trade decisions remain yours.
— 🌐 Works on all markets and timeframes. Instruments without volume data are handled automatically (VWMA falls back to EMA, the volume filter bypasses, scoring uses a neutral volume component).
The indicator is completely free. Indicator
Auto-ATR Volatility Spike & Trend Tracker [BigBeluga]Auto-ATR Volatility Spike & Trend Tracker is an institutional-grade algorithmic trend-following terminal engineered for PulseWire. It is specifically built to isolate high-momentum breakout anomalies (spikes) from ordinary noise and anchor a dynamic, risk-managed trailing stop-loss directly to the underlying structural expansion.
By merging volumetric price momentum with an adaptive Average True Range (ATR) detection framework, this indicator completely redefines how breakout traders enter and manage trends. Instead of reacting blindly to standard moving average crosses, the system utilizes an execution state machine that locks onto systemic market expansion, tracks trend health via dynamic midpoint lines, and protects capital with a trailing protection line.
🔵 CHANNELS & ARCHITECTURAL CORE ENGINE FEATURES
1. Dual-Mode Spike Detection System
Auto ATR Volatility Engine: Automatically adapts to varying market conditions. By cross-referencing incoming candle structures against an ATR Length multiplier baseline, the indicator filters out flat consolidation periods and flags abnormal, high-liquidity volume expansions that signify true institutional participant footprints.
Fixed Percentage Breakout Mode: For traders operating in highly structured assets with predictable daily limits, this module locks onto absolute price change thresholds ( Fixed Spike Threshold % ), isolating momentum moves that pierce predefined parameters.
Wick-to-Body Range Toggle: Allows you to switch calculations to run from either the raw candle body (Open to Close) or the full extreme range ( Calculate From Wicks (High/Low) ). This isolates clean structural closes while adjusting to high-volatility liquidity sweeps.
2. Predictive Mid-Level Benchmarks & Spacing Visuals
Dynamic Mid Level Dash Lines: When a valid trend spike is verified, the engine immediately draws a horizontal midpoint line extending from the center of the candle ( Display Mid Level Dash Line ). This centerline serves as an immediate structural macro floor or ceiling; as long as price retains this boundary, the primary breakout impulse remains historically intact.
Measurement Arrow Guides & Measurement Labels: Automatically draws measurement arrow guides along with real-time text percentage indicators directly over the breakout candle ( Display Size % Labels & Arrow Lines ). This gives you instant clarity on the volatility profile without needing to use manual drawing tools.
3. Algorithmic State Machine & Trailing Protection
Volatility-Adjusted Trailing Stops: Once a breakout trend is established, the indicator deploys a step-calculated trailing line based on your Trailing ATR Multiplier . This line is engineered to trail tightly beneath bullish expansions or above bearish flushes, keeping you safely in the macro trend while mitigating downside variance.
Trend Interlock Protection: The underlying state machine features built-in trigger restrictions that lock execution while a trend is dominant. This prevents counter-trend false entries or premature reversals, keeping your focus strictly on the dominant structural path.
Theme Overwrite Candlesticks: Completely recolors the active layout chart workspace bars using vivid, customized hex-theme presets ( Bullish/Bearish Theme Colors ) the exact moment an abnormal spike is validated.
4. Persistent Macro Statistics Dashboard Matrix
Top-Right Analytics HUD Table: Instantly maps out a high-performance database grid showing critical data points from the most recent historical market expansions.
Real-Time Metrics Monitoring: Explicitly stores and displays the precise directional Spike Type , Size (%) , and exact entry execution Price for both bullish and bearish cycles, providing a reliable quantitative snapshot of the asset's structural strength.
🔵 SYSTEMATIC EXECUTION STRATEGIES & RISK INTERPRETATION
Midpoint Re-test Accumulation Plays: When a powerful up-spike forces a market breakout, do not chase the initial overextended move. Instead, wait for a constructive pullback toward the extended dynamic dashed midline. If price builds a base and prints a clean rejection candle at this level, it signals a premium, low-risk continuation entry aligned with institutional order flow.
Trailing ATR Invalidation Exits: The trailing stop-loss line acts as your absolute trend line invalidation boundary. In a powerful bullish expansion, the indicator will continuously trail and lock in accrued profit beneath the recent low points. A clean daily close crossing beneath this line confirms an official trend termination, signaling an immediate exit to protect your capital.
Breakout Sizing Divergences: Cross-reference the live metrics dashboard data to spot exhausting trends. If an asset is pressing higher but newly generated bullish spikes show smaller percentage sizes compared to the historical records on your HUD table, it exposes fading momentum—frequently warning of an impending reversal or structural distribution phase.
🔵 INTERFACE CONFIGURATION AND PARAMETERS
Detection Mode Controls: Choose between Auto ATR or Fixed % settings and specify lookback periods to customize the indicator to match any asset class, volatility cycle, or execution chart timeframe.
Visibility Filters Overrides: Independently toggle midlines, trailing stops, background cloud color fills, or measurement labels to maintain a clean, distraction-free charting interface.
Theme Personalization Modifiers: Fully adjust color properties for upward spikes, downward spikes, buy/sell arrows, and trailing lines to blend seamlessly into your dark or light workspace layout themes.
Transform your charting workspace from speculative guessing into an automated, volatility-tracked breakout environment with the Auto-ATR Volatility Spike & Trend Tracker terminal. Indicator
MTF Trend Context
MTF Trend Context is a decision-support panel that answers one question before you trade: does the current context allow a trade at all? It does not generate entry signals — it tells you when trend alignment, trend strength, distance from value, volatility and time of day justify looking for one, and tells you to stand aside the rest of the time.
WHAT IT DOES
It reads the trend on your chart timeframe plus two higher timeframes and condenses everything into a single verdict at the bottom of the panel:
🟢 LONGS ONLY — all three timeframes aligned up and the market is trending
🔴 SHORTS ONLY — all three timeframes aligned down and the market is trending
🟡 STRETCHED — WAIT PULLBACK — aligned, but price is too far from VWAP to chase
🟡 CONFLICT — WAIT — timeframes disagree
⛔ RANGE — NO TRADE — ADX below threshold
⛔ OFF HOURS — NO TRADE — outside your personal trading window (optional filter)
HOW IT WORKS
Trend score per timeframe: three conditions worth ±1 each — price vs fast EMA (20), fast EMA vs slow EMA (50), and price vs session VWAP. A full score on the chart timeframe plus agreement on both higher timeframes is required for alignment. Higher timeframes are picked automatically (5m → 15m + 1h, 15m → 1h + 4h, etc.) or set manually. On daily and higher timeframes the VWAP component is excluded automatically and the maximum score adjusts accordingly.
Range filter: when ADX on the chart timeframe is below the threshold (default 20) the verdict is forced to RANGE regardless of alignment. Trend strength is shown as a 5-block bar (ADX 10 → empty, ADX 40 → full).
Stretched price (anti-FOMO): the session VWAP is anchored to the daily session open (on CME futures, the 18:00 ET Globex open) with ±1σ and ±2σ bands. Beyond 2σ the price is considered stretched and the verdict switches to WAIT PULLBACK.
Volatility with a time-of-day baseline: the current ATR is compared against its own average at the same time of day over the last N sessions (default 10), not against a flat rolling average. Intraday volatility is strongly seasonal — a flat average would make quiet sessions such as Asia read "low" permanently. 100% = normal for this time of day. It needs roughly N sessions of chart history to fill in.
Daily levels: previous day high, low, close and the current session open, drawn only for the current session with optional name labels. The panel shows the nearest level, its distance and direction, and warns when a level sits in the way of a trade.
Trend age: bars since the current alignment started, classified as young / mature / late, so you know whether you are early or chasing.
Trading-hours filter (optional): define your own window and timezone; outside it the verdict is NO TRADE and all alerts are muted.
Session row: shows whether Asia, London or New York is active.
NON-REPAINTING
Higher-timeframe readings use the last CONFIRMED higher-timeframe bar (request.security with a offset and lookahead), so the values shown on historical bars are exactly what you would have seen live. The cost is one higher-timeframe bar of lag; the benefit is an honest history.
ALERTS
Three alert conditions — traffic light GREEN (longs), traffic light RED (shorts), and entering RANGE — plus matching alert() events, so a single alert with "Any alert() function call" covers everything. Recommended trigger: "Once per bar close".
SETTINGS
Every chart element (EMAs, EMA cloud, VWAP line and bands, stretched-zone fill, level lines and labels) has its own visibility toggle, color and width. Panel rows can be hidden one by one; panel position and text size are configurable.
NOTES AND LIMITATIONS
Designed with CME index futures on intraday charts in mind; works on any symbol, but on 24/7 markets the "day" follows the exchange's daily bar.
Defaults are tuned for 5-minute charts. On quiet sessions consider lowering the ADX threshold to 17–18.
This is a context filter, not a strategy. It does not tell you where to enter or exit, and a green or red verdict is not a prediction about any individual trade. Indicator
Adaptive Regression Breakout Map | GainzAlgoThe Adaptive Regression Breakout Map (ARBM) is an advanced volatility and trend-tracking system designed to identify periods of extreme market compression and automatically map out high-probability breakout trades.
Rather than relying on traditional lagging indicators, ARBM utilizes a continuous statistical baseline to measure market "squeezes." Once a breakout is confirmed, the indicator shifts from analysis into execution mode, drawing a dynamic visual map on your chart that outlines precise Entry, Stop Loss, and Take Profit (TP1, TP2, TP3) levels, complete with automated trailing stop logic and a live performance dashboard.
How It Works
At its core, the ARBM operates on a dual-engine architecture:
Statistical Compression (The Squeeze): The script calculates a rolling linear regression baseline and wraps it in standard deviation bands. It continuously measures the width of this channel and compares it to a historical lookback period. When the bandwidth drops into a historically low percentile, the bands change color, signaling that the market is in a "squeeze" and building energy for a move.
Auto-Trendlines: Alongside the statistical bands, the script plots dynamic, auto-trendlines across recent pivot highs (cyan) and lows (magenta). These holographic lines track geometric compression and leave a visual history on the chart.
The Breakout Trigger: A signal is generated when the price violently escapes either the statistical standard deviation bands or the geometric auto-trendlines while the market is in a confirmed contraction state.
Dynamic Trade Mapping: Upon a breakout, the script calculates targets based on the volatility (bandwidth) at the time of the breakout. It plots the trade directly on your chart and actively trails the stop loss as targets are hit.
The Settings and Selections
The indicator is highly customizable, divided into four primary control groups:
Regression Model:
Regression Length: The lookback period for the linear regression baseline.
Deviation Multiplier: The width of the statistical bands (similar to Bollinger Bands).
Contraction Metrics:
Lookback Period: How far back the script looks to determine if the current channel is historically narrow.
Contraction Threshold %: The percentile the bandwidth must drop below to trigger a "squeeze" state.
Target Architecture:
TP1, TP2, TP3 Multipliers: Determines how far away your take profit targets are, dynamically scaled by multiplying the width of the channel at the time of the breakout.
Trendlines Overlay:
Show Holographic Trendlines: Toggle the geometric trendlines on or off.
Pivot Length: Determines how sensitive the script is when identifying the swing highs and lows used to draw the trendlines.
How to Use It
Trading with the ARBM is highly visual and systematic:
Wait for the Squeeze: Watch the regression channel. When the bands turn gray, volatility has compressed, and the market is consolidating.
Wait for the Signal: Look for a "Breakout, Long" or "Breakout, Short" label to appear. This confirms price has broken structure with momentum.
Follow the Map: The script will immediately draw your Entry (Blue), Stop Loss (Red), and three Take Profit targets (Green dashed lines).
Manage the Trade: The indicator handles trade management visually.
When TP1 is hit, the Stop Loss line automatically moves to your Entry price (Breakeven), and a label confirms the trail.
When TP2 is hit, the Stop Loss trails to TP1.
When TP2 is hit, the Stop Loss trails to TP1.
The trade closes entirely if TP3 or the trailing stop is hit. (Note: Hitting TP1 secures a win for the system's tracking, even if the remainder is stopped out at breakeven).
Monitor Performance: A stylized dashboard in the top right corner tracks the total number of signals, the historical Win Rate, and the Trade-by-Trade Sharpe Ratio, allowing you to quickly validate the settings for any given asset or timeframe.
Final Thoughts
The Adaptive Regression Breakout Map removes the guesswork from breakout trading. By combining continuous statistical volatility tracking with futuristic geometric trendlines, it mathematically identifies when a market is ready to move. Furthermore, by drawing the exact risk-to-reward parameters on the chart and tracking its own historical performance, it forces strict risk management and objective trade execution.
Indicator
Adaptive Trend Rails [NICK789]Adaptive Trend Rails
OVERVIEW
Adaptive Trend Rails is a market-structure and break-and-retest framework built around one shared price channel. It is designed to answer four practical questions:
1. Which direction currently controls the chart?
2. What exact price level would confirm continuation or a trend change?
3. Is pressure building against the active trend before that change is confirmed?
4. Has price completed a valid breakout, retest and rejection sequence that can be turned into a structured trade plan?
This is not a collection of unrelated indicators placed on the same chart. The rail engine is the foundation of the script, and every additional component—equilibrium, reversal pressure, trend-change quality, multi-timeframe context and the break-and-retest plan—uses information derived from that same structure.
CORE RAIL ENGINE
The script builds an upper and lower rail from the highest high and lowest low of an adaptive lookback. The lookback changes according to the chart timeframe, while the user-selected Narrow, Medium or Wide setting adjusts how quickly the rails react.
A bullish break occurs when price crosses above the previous upper rail. A bearish break occurs when price crosses below the previous lower rail.
The script then classifies each break according to the existing trend state:
• A break in the current direction is treated as continuation.
• A break against the current direction is treated as a trend change.
Because the decision level is taken from the previous rail value rather than the rail currently expanding with price, users can see the actual level that must be crossed. The live “Continue?” and “Trend Change?” guides therefore act as decision levels, not predicted targets.
ADAPTIVE EQUILIBRIUM
The centre line is not a simple midpoint or fixed moving average.
First, the script measures where price is positioned between the active upper and lower rails. That normalized position is then smoothed using EMA and volume-weighted information, with a WMA fallback when volume-weighted data is unavailable. The accepted position is shifted toward the centre and constrained so the equilibrium cannot sit directly on the outer rails.
The resulting line represents an adaptive accepted-value area inside the current structure.
Equilibrium is used throughout the script:
• Its slope helps determine whether internal momentum is rising or falling.
• Its curl helps identify a possible change in pressure.
• Retest plans require price to remain on the correct side of equilibrium.
• Optional entry filtering can require equilibrium to slope in the proposed trade direction.
• A pending retest is cancelled when price loses the required equilibrium relationship.
For this reason, equilibrium is part of the calculation engine and not merely a decorative average.
REVERSAL-PRESSURE WARNINGS
The yellow reversal dots are early warnings, not reversal signals.
While a trend is active, the script measures opposing pressure using a weighted combination of:
• Candle closing location
• Upper or lower wick rejection
• Directional candle-body strength
• Relative volume participation
• Relative candle-range expansion
• Equilibrium slope or curl
• Price location within the rail structure
A bearish warning is only considered while the rail trend is bullish and price is positioned in the upper portion of the structure. A bullish warning is only considered while the rail trend is bearish and price is positioned in the lower portion.
The warning means pressure is building against the current trend. It does not change the trend by itself. Price must still close through the displayed Trend Change level before the rail state is considered reversed.
A cooldown is applied to prevent repeated warning dots from being printed on every nearby candle.
TREND-CHANGE QUALITY
When a confirmed trend change occurs, the script assigns a compact quality reading based on the breakout candle.
The score combines:
• Relative volume
• Relative candle range
• Directional body strength
• Closing location in the breakout direction
The resulting label is shown as Weak, Moderate, Good or Strong.
The tooltip also describes the character of the breakout, such as Clean Break, Expansion, Absorption, Weak Close or Low Participation. This is intended to provide context, not to guarantee that a strong-rated break will continue.
MULTI-TIMEFRAME CONTEXT
The horizontal trend strip rebuilds the same rail-state method across nine timeframes:
1 minute, 5 minutes, 15 minutes, 30 minutes, 1 hour, 2 hours, 4 hours, 1 day and 1 week.
This is important because the table is not mixing unrelated moving-average or oscillator definitions. Every timeframe is evaluated with the same upper-rail/lower-rail breakout method used on the chart.
The script also assigns a practical paired timeframe to the active chart—for example, a 1-minute chart is paired with 5 minutes, a 5-minute chart with 15 minutes, and a 15-minute chart with 1 hour.
Paired-timeframe information is warning-only. It does not silently block, delay or change an entry. When a plan triggers against the paired rail trend, the table and dedicated alert identify that conflict so the trader can make the final decision.
BREAK-AND-RETEST PLAN
The optional trade-plan engine does not enter immediately when a rail breaks.
Its sequence is:
1. Price closes through a continuation or trend-change level.
2. The exact broken rail level is stored.
3. Price must return on a later candle and touch or sweep that level.
4. The candle must reject the level and close back through it in the breakout direction.
5. Price must remain on the correct side of equilibrium.
6. Optional filters check equilibrium slope and whether the rail structure is wide enough relative to the configured stop distance.
All confirmed setups are labelled simply as “RETEST” to avoid implying that one setup carries a guaranteed grade or outcome. The tooltip still identifies whether the retest followed a Trend Change or a Continuation break.
The user may enable both setup types or restrict the engine to trend changes, continuations, longs or shorts.
Pending setups expire after the selected number of bars. They are also cancelled when the rail trend changes or price invalidates the required equilibrium relationship. This prevents an old breakout level from remaining armed after its original context has disappeared.
RISK AND PLAN DISPLAY
When a retest entry is confirmed, the script can display:
• Entry level
• ATR-adaptive or fixed-tick stop
• Reward/risk or fixed-tick target
• Active-plan direction
• Target-hit or stop-hit result
The default ATR Adaptive method scales the stop to current volatility and calculates the target from the selected reward/risk ratio. This makes the plan transferable across forex, metals, crypto, stocks and futures even when their price increments differ. A Fixed Ticks mode remains available for traders who intentionally use exchange tick distances on instruments such as futures. All values remain examples and must be adjusted for the instrument, timeframe and personal risk limits.
The tool is an indicator, not an automated strategy. It does not calculate position size, brokerage fees, commissions, spread or slippage, and it does not place orders.
HISTORICAL REVIEW
Historical plans and review statistics are optional and disabled by default.
The review panel counts completed target and stop outcomes visible in the loaded chart data and reports the net result in R-multiples. Replaced plans are excluded. If both the target and stop are touched within the same ordinary chart candle, the script records the stop first because the true intrabar sequence cannot be known from standard OHLC data.
Win rate is hidden until a minimum sample is available. These statistics are intended for chart review and configuration comparison only. They are not a full strategy backtest and should not be presented as expected future performance.
HOW TO USE
A simple workflow is:
1. Select Narrow, Medium or Wide rails according to the desired reaction speed.
2. Read the active rail colour to identify the current structural direction.
3. Use the Continue and Trend Change levels as the prices that would confirm the next structural event.
4. Treat reversal dots as preparation warnings only.
5. Use the quality label to inspect the participation and candle character of a confirmed trend change.
6. Check the multi-timeframe strip for broader alignment or conflict.
7. Enable the Break & Retest Plan when structured retest signals, ATR-adaptive or fixed-tick levels and review tools are required.
8. Adjust stop and target ticks for the traded symbol rather than assuming the defaults fit every market.
DEFAULT DISPLAY
The default view focuses on the rails, adaptive equilibrium, live decision levels, trend-change quality and multi-timeframe context.
Candle colouring, the trade-plan engine, historical plans and review statistics are optional so users can keep the chart clean and enable only the tools relevant to their workflow.
ALERTS
Alerts are provided for:
• Bullish and bearish continuation
• Bullish and bearish trend change
• Bullish and bearish reversal pressure
• Long and short break-and-retest entries
• Entries against the paired timeframe
• Replacement of an unresolved plan by an opposite valid setup
• Target hit
• Stop hit
Confirmed continuation, trend-change and retest-entry alerts are intended for candle-close use. Reversal-pressure warnings are intentionally earlier and should always be treated as unconfirmed until the relevant Trend Change level is closed through.
LIMITATIONS
Adaptive Trend Rails is a structure and planning tool, not a prediction engine.
Rail breaks can fail, strong breakout candles can reverse, and multi-timeframe alignment does not guarantee continuation. ATR-based distances expand and contract with recent volatility, while fixed-tick distances behave differently across instruments and feeds. Historical review results are displayed in R-multiples and depend on the loaded chart, selected settings and available OHLC data.
Users should combine the tool with their own risk management, market-session awareness and execution rules.
ORIGINAL CONTRIBUTION
The original purpose of this script is to turn one adaptive rail structure into a complete decision sequence:
current trend → live confirmation level → opposing-pressure warning → confirmed structural break → quality context → multi-timeframe comparison → delayed retest validation → risk-plan display → optional historical review.
Each component exists to explain or validate another part of that sequence. The script is therefore designed as one integrated framework rather than a mashup of independent indicators. Indicator
Trendline Architect [Quantum Algo]Trendline Architect
====================================================
🔶 OVERVIEW
Trendline Architect is an automatic trendline indicator that does what most trendline tools skip: it validates every line before drawing it, makes each line earn its status through real touches, grades every breakout by quality, and then automates the break-and-retest sequence that trendline traders normally track by hand. Lines are born as dotted candidates, promoted to solid confirmed trendlines only after the market validates them with a third touch, graded on breakout, kept on a retest watch after they break, and paired into parallel channels automatically — all with a deliberately quiet chart: one-letter signals whose full context lives in hover tooltips.
The problem this script solves is trendline spaghetti and trendline noise. Automatic trendline tools typically draw every pivot-to-pivot connection and alert on every violation. This engine rejects invalid lines at birth, refuses duplicates, caps how many lines can exist per side, silences the breaks of unproven lines by default, and filters weak breakouts by grade — so what remains on the chart is only what the market has actually respected.
🔶 WHAT IS A TRENDLINE BREAK AND RETEST?
A trendline connects successive swing points and acts as dynamic support or resistance while price respects it. A breakout occurs when price closes decisively through the line. The retest is what disciplined traders wait for next: price returning to the broken line from the other side and rejecting — old support acting as new resistance, or old resistance reclaimed as support. That return-and-reject is one of the most traded patterns in classical charting, and this engine detects the entire sequence automatically: validated line, graded break, watch window, confirmed retest.
🔶 WHY THIS SCRIPT IS ORIGINAL
1. Geometric validity at birth. A candidate line is rejected before it is ever drawn if any candle close violated the segment between its two anchor pivots. Lines that were never respected never reach the chart.
2. Touch-earned lifecycle. Every line starts as a dotted, untagged candidate. Each validated touch — a wick into tolerance with a close that respects the line — is counted, and only at the configured touch count is the line promoted: solid, thicker, fully colored, with a live ×N touch tag. The chart itself shows which lines the market obeys.
3. Anti-spaghetti engineering. Duplicate candidates with similar slope and position are refused, each side is capped at a configurable number of active lines with the weakest evicted first, and stale lines expire by age. The chart stays readable on every timeframe.
4. Breakout quality grading. Every breakout is scored from three observable components — volume z-score, penetration depth in Average True Range units, and breakout candle body ratio — into grades A, B, and C. Grade A signals highlight in the accent color.
5. A retest engine. Broken lines are not deleted; they turn into gray watch lines for a configurable window. A return to the broken line with a rejecting close prints the Retest signal — the classic polarity flip, automated.
6. Silence by default, depth on demand. Signals print as single letters — B for breakout, R for retest — with the full context (direction, grade, volume, penetration) in the hover tooltip. Two noise filters ship enabled: breaks of unconfirmed lines retire silently, and breakouts below a minimum grade stay off the chart and out of the alerts.
7. Automatic channel detection. When an active support line and resistance line run parallel within a slope tolerance, the engine fills the channel between them and reports it on the dashboard.
8. A live architecture dashboard. Active support and resistance counts, the nearest line with its distance in Average True Range units, a trend read derived from confirmed line slopes, the last break grade, the retest watch count, and channel status — in a compact, fully themeable panel.
🔶 HOW IT WORKS
Line construction: Confirmed swing pivots anchor every candidate line. Each new pivot is paired with the previous same-side pivot, the segment is checked for historical violations, duplicates are rejected, and side capacity is enforced before the line is created.
Touch validation: A touch counts only when the wick enters the tolerance band around the line and the close still respects it. Touches accumulate on the line's tag; the confirming touch promotes the line and, from that point, validated touches are marked with dots.
Breakouts: A close through the line beyond the buffer triggers the break. Confirmed lines produce graded signals; forming lines retire silently when the default filter is on. The broken line converts to a gray dashed watch line.
Retests: Within the watch window, a return to the broken line with a rejecting close prints R — upward reclaim of broken resistance, or downward rejection at broken support. Watch lines that see no retest expire quietly.
Channels: Active opposite-side lines are compared by slope; the closest parallel pair within tolerance is filled as a channel.
Non-repainting: Pivots require confirmation, and all touches, promotions, breaks, and retests are evaluated on closed bars only. Once printed, nothing moves.
Chart hygiene: Completed lines, touch dots, and signals are all capped by input, keeping the chart clean and the auto-scale anchored to current price.
🔶 HOW TO USE IT
1. Works on any market — cryptocurrency, forex, gold, indices, stocks, futures — and any timeframe. Raise the pivot length for larger structures.
2. Trust the visual hierarchy: dotted lines are candidates, solid lines with ×N tags are market-validated, gray dashed lines are broken and on retest watch.
3. Treat B signals as regime information: grade A breakouts with volume and penetration carry far more weight than the minimum-grade ones, and the grade is one hover away.
4. The R signal is the classic entry location: the broken line has flipped roles and price has confirmed the flip. Stops belong on the far side of the retested line.
5. Use the dashboard's Nearest row to know how far price is from the closest active line in Average True Range units before it gets there.
6. If you want the raw, unfiltered feed, disable the two noise filters in Signals — the engine detects everything either way.
🔶 SETTINGS
- Detection: pivot length, maximum anchor span, active lines per side, line expiry, completed lines to keep.
- Touches, breaks and retests: touch tolerance, touches to confirm, breakout buffer, retest watch window.
- Signals: breakout and retest toggles, confirmed-lines-only filter, minimum breakout grade.
- Channel detection with slope similarity tolerance.
- Full color customization, extension length, touch dots toggle.
- Themeable dashboard: position, four text sizes, title band, background, frame, grid, and three text colors.
🔶 ALERTS
- Trendline Confirmed — a line collected its confirming touch.
- Bullish / Bearish Trendline Breakout — a qualified close through a line, honoring the grade filter.
- Bullish / Bearish Retest Confirmed — a broken line was retested and rejected.
- Parallel Channel Detected — an active support and resistance pair is running as a channel.
🔶 FREQUENTLY ASKED QUESTIONS
Does the indicator repaint? No. Anchors are confirmed pivots and every touch, break, and retest is evaluated at bar close. Pivot confirmation introduces intentional lag equal to the pivot length.
Why do I see so few lines? By design. Between geometric validation, duplicate rejection, side caps, and expiry, only lines with genuine market respect survive. Raise the per-side cap or lower the confirmation count for a busier chart.
What do B and R mean? B is a graded breakout and R is a confirmed retest of the broken line. Hover either label for direction, grade, volume, and penetration details.
Why did a breakout print no signal? Either the line was still unconfirmed while the confirmed-only filter is on, or the break graded below your minimum. The line still changed state; only the signal was filtered.
What makes a grade A breakout? Elevated volume, deep penetration beyond the line in Average True Range terms, and a strong-bodied breakout candle — all three together.
🔶 CREDITS
Trendline analysis, breakout trading, and the break-and-retest pattern are classical charting techniques in the public domain, refined by generations of technicians. This script gratefully acknowledges that shared lineage. The geometric validity engine, touch-earned lifecycle, breakout grading model, retest watch engine, channel detection, noise-filtering architecture, and all code in this script are original work — no third-party or open-source script code was reused.
🔶 LIMITATIONS
Trendlines are geometry, not guarantees: valid lines break and graded breakouts fail. Pivot confirmation delays anchor recognition by design. Volume grading is less meaningful on symbols with unreliable volume reporting. Channel detection reports the closest parallel pair, not every possible channel. No indicator replaces independent analysis.
🔶 DISCLAIMER
This script is provided strictly for educational and informational purposes. It is not financial advice, an investment recommendation, or a solicitation to buy or sell any financial instrument. Past behavior of any trendline, breakout, or retest does not guarantee future results. Trading involves substantial risk. Always do your own research and manage risk independently.
Indicator
AlgoZ Pro Price ActionAlgoZ Pro Price Action is a clean price action based forex indicator built to help traders identify potential Buy, Sell, and Exit areas using a combination of market structure, trend filtering, volatility logic, and dynamic trade management.
This indicator is designed around the idea that not every trade needs to have a high win rate to be useful. Instead of only looking for quick scalp targets, AlgoZ Pro Price Action is built to manage trades with a runner-style approach. The goal is to cut weak trades faster, protect trades that start moving in the right direction, and allow stronger moves to continue when momentum is present.
The default settings are best suited for 1-minute EUR/USD forex trading. Other forex pairs and timeframes may work differently and should be tested before use.
The indicator uses market structure breaks to identify possible directional shifts. When price breaks key internal support or resistance levels, the script checks multiple filters before plotting a signal. These filters are designed to reduce low-quality signals during chop, weak momentum, or overextended conditions.
AlgoZ Pro Price Action includes Buy, Sell, and Exit labels directly on the chart. Buy signals are shown in teal, Sell signals are shown in pink, and Exit signals are shown in a neutral color. The bars can also be colored based on the active signal direction so it is easier to visually track the current market bias.
One of the main parts of this indicator is the trend lock system. The trend lock helps prevent the indicator from flipping back and forth too quickly during noisy market conditions. It uses EMA trend structure, slope behavior, and confirmation bars to decide whether the market is currently favoring Buy-side or Sell-side continuation. Countertrend signals must be stronger before they are allowed through, which helps reduce random reversal signals during an active move.
The indicator also includes automatic forex pair adjustment. It detects whether the chart is a JPY pair or a non-JPY forex pair and automatically adjusts pip size calculations. This helps prevent issues where a stop or exit calculation is too tight or too wide because of the symbol’s price format. The script also includes auto volatility tuning, which uses ATR-based logic to scale stop size, runner triggers, trailing stop distance, dead-trade protection, and cooldown behavior based on the current pair’s movement.
Trade management is handled through a dynamic exit engine. Instead of using only fixed take profit levels, the indicator uses runner logic. Once a trade moves far enough in profit, the trade can enter runner mode. From there, the script can move the stop, protect profit, and trail the trade if the move continues. This allows stronger trades to breathe while still giving the indicator a way to exit when momentum fades.
AlgoZ Pro Price Action also includes dead-trade protection. If a trade has been open for a certain number of bars and has failed to make meaningful progress, the script can plot an Exit signal. This is designed to help remove weak trades that are not moving enough to justify staying in them.
The indicator includes several optional filters and controls, including EMA trend filtering, ADX strength filtering, chop filtering, candle body quality filtering, minimum EMA separation, price distance from the slow EMA, overextension protection, post-exit cooldown, and emergency protection logic.
Main features include:
• Buy, Sell, and Exit labels
• Teal and pink AlgoZ Pro visual theme
• Price action and market structure based signals
• Internal support and resistance break logic
• Optional BOS / CHoCH structure markings
• EMA trend filtering
• ADX trend strength filter
• Chop and range filter
• Candle quality filter
• Trend lock system
• Countertrend signal protection
• Auto pip size detection
• Auto adjustment for JPY and non-JPY forex pairs
• ATR-based auto pair tuning
• Dynamic stop logic
• Runner-style trade management
• Breakeven / profit lock logic
• Trailing stop logic for stronger moves
• Dead-trade exit protection
• Optional bar coloring
• Optional entry and stop lines
• Optional status table
Recommended default use:
1-minute EUR/USD forex chart.
Other forex pairs and timeframes may require adjustment depending on spread, volatility, session, and market conditions. Indicator
SmartTraders Research Labs -Geometric Trend Lines - GTLGEOMETRIC TREND LINES (GTL)
GTL is a research indicator that studies the geometry of price structures. It freezes structural anchors in the past, stretches two right-triangles between those anchors and the live candle, and reads their angles inside a dimensionless coordinate space — then learns from every completed structure to estimate, with calibrated statistics, which way the current one is leaning. It is a structural analysis and research tool, not a trading system.
█ STEP OUT OF THE CHART PLANE
Every trader has drawn a trendline and called it steep. Steep compared to what? Stretch the chart window and the angle flattens. Jump from Bitcoin to a quiet blue-chip stock and a "45-degree rally" becomes a completely different animal. The chart plane mixes two quantities that were never meant to share axes — price and time — so any angle drawn on it is a property of your zoom level, not of the market.
My standard, before any geometry begins, is to take the shape out of the chart plane entirely. GTL maps every point into an Isotropic Coordinate System (ICS) where both axes are pure numbers:
y = log(price) / σ
x = bars / lookback
Price is expressed in units of the instrument's own volatility (σ, estimated with the Yang-Zhang method over 500 bars), and time in units of the analysis window. Nothing on either axis carries dollars, lira, satoshis or minutes anymore.
In this space, a degree finally means something. The angle
θ = atan(Δy / Δx) × 180 / π
is intrinsic: a 60° ceiling angle on gold's 30-minute chart describes the same geometric event as a 60° ceiling angle on a 3-minute meme-coin chart. The instrument's personality — its price level, its tick size, its temperament — has been normalized away, and what remains is pure trajectory. Everything else in this indicator stands on that ground.
The same rally, two zoom levels, two different angles — and on the right, the dimensionless ICS home where θ finally becomes a property of the market, not of your screen.
█ THE TRIANGLE — A SHAPE THAT CARRIES DATA
Of all the shapes humanity has leaned on, the triangle is the one that never let us down. It raised the pyramids, it holds every bridge truss and roof frame you have ever walked under, and it is the only polygon that cannot be deformed without changing the length of a side. Engineers call that property rigidity. I read it as trustworthiness — a triangle does not lie about its geometry.
That is why I chose it as the measuring instrument. On every structure, GTL constructs two right-triangles inside ICS:
The ceiling triangle — from the frozen HH anchor to the live candle's high.
The floor triangle — from the frozen LL anchor to the live candle's low.
Each triangle is not a drawing; it is a container. Four measurements live inside it at every bar:
θ — the signed angle of the hypotenuse, the indicator's core reading
Δy — the signed magnitude of the move in volatility units
area — the geometric surface the structure has swept
centroid — the shape's center of mass in ICS
While price grinds below a frozen ceiling, the ceiling angle sinks degree by degree into negative territory. When price presses up from a frozen floor, the floor angle climbs. Two triangles breathe with the market — one watching from above, one from below — and their angles are the raw language everything downstream of this indicator speaks.
One triangle watches from above, one from below — and θ, Δy, area and centroid live inside each of them.
█ AN ANCHOR IN THE PAST — MEASURING FROM CALM WATER
Picture a storm at sea, and two people trying to measure the waves. One stands on the shore. One sits in a boat, right among them. The observer on the shore, feet on solid ground, reads the height of every wave with precision — however wild the water gets, the ground beneath him does not move. The observer in the boat rises and falls with the very thing he is trying to measure; every number he writes down is contaminated by his own motion.
Most swing-based tools are the observer in the boat. Their reference points — the latest swing high, the latest swing low — are redefined by the market again and again, so any angle or distance measured from them mixes two movements at once: the price's, and the reference's own.
GTL plants its observer on the shore. At the birth of every structure, the highest high and the lowest low of the lookback window are frozen — locked to a fixed bar in the past — and from that moment they do not move. Every angle is measured from calm, settled water toward the storm of the live candle. The reading stays pure: when θ changes, it is because price moved, and for no other reason.
The anchors hold until price closes beyond one of them. That close is the break — the moment the structure completes, is archived with its full geometry, and a fresh pair of anchors freezes for the next chapter.
One naming note, so the chart reads correctly: what GTL labels HH and LL are these frozen anchor levels, not the traditional trailing swing highs and lows.
Solid ground measures the storm precisely; a boat measures mostly itself — GTL is the observer on the shore, and the frozen box below is exactly that shore.
█ WHY 23 — A PRIME WINDOW
The lookback window — the number of bars GTL scans before freezing a new pair of anchors — defaults to 23. The choice is arithmetic, not aesthetic.
23 is prime: its only divisors are 1 and itself. Stated as a condition,
gcd(23, k) = 1 for every k < 23
For a rolling window, that matters mechanically. If a periodic component of length k shorter than the window is present in the data, the window boundary does not keep meeting that component at the same phase. Because 23 and k are coprime, the alignment steps through all k possible phase offsets before it repeats. A composite window gives that protection away: 24 divides cleanly by 2, 3, 4, 6, 8 and 12, so components at those lengths can meet repeated window boundaries at the same phase, allowing anchor placement to inherit regularity from the measuring frame itself.
Engineering solved the same problem with hunting-tooth gear design: tooth counts are chosen coprime so each tooth eventually meshes with every counterpart, instead of the same pairs meeting forever and wearing a repeated pattern into the metal. Periodical cicadas offer a biological analogy — 13- and 17-year emergence cycles, both prime, reduce overlap with shorter recurring cycles.
This is a design principle stated in number theory, not a performance claim. A prime window does not make GTL better by itself, and it does not prove anything about future price. It simply reduces one avoidable source of arithmetic resonance, so repetition in the readings is less likely to be created by the measuring window. The lookback remains a user input; 23 is the default I stand behind.
Every window from 20 to 25 shares a divisor with at least one shorter cycle length — 23 is the only empty row, which is exactly why it is the default.
█ HOW THIS SERIES IS BUILT — CSV OUT, ANALYSIS IN
This episode follows a working method I now treat as the standard for the whole series: nothing ships on intuition alone. The indicator exports its own internal life — every angle, every structure, every break — as plain columns in the Data Window, ready for CSV export. Before publication, those exports were analyzed with AI assistance across a deliberately diverse panel:
7 instruments × 2 timeframes = 14 datasets
gold, Bitcoin, Tesla, Brent crude, Turkish Airlines, Dogecoin, Saudi Aramco
30-minute and 3-minute bars — roughly 550,000 bars, ~30,000 completed structures
What came back from that study entered the code as design decisions, not as promises. Exactly five constants in the learning layer are hard-coded. They are not presented as universal truths or performance guarantees; they are documented design constants selected from the development study and kept fixed so the live model remains transparent and reproducible:
CAL_LAMBDA = 0.999 — fading-factor decay for the calibration counters
CAL_JUMPTH = 2.0 — empirical jumpiness threshold between steady and choppy estimates
CAL_MINW = 30 — minimum effective sample weight before a calibration cell is trusted
CAL_ROLL = 20 — length of the live recent-record window
JUMP_WIN = 5 — bars used for the short-term stability measurement
The methods behind the layer are standard enough to be named — fading-factor prequential counting for online calibration, adaptive Gaussian KDE for local probability estimation, and Kish-style effective sample size for weighted evidence — and the next section walks through each of them with its reference. The fixed values above are GTL's calibrated defaults from that study, not claims that these numbers are optimal for every market, symbol, or timeframe. Everything else the statistics need — bandwidth, confidence, significance — is computed live from the chart's own history.
Two honest disclosures. First, this analysis is development documentation, not an independent audit, and this description makes no accuracy claims from it. Second, the same door is open to you: every column used in that study is exported by the script itself, so you can pull the CSV from your own chart and put the same questions to any tool you trust.
The build loop of this series: the script exports its own life as CSV, analysis turns it into five documented design constants, and the same door stays open to every user.
█ FROM GEOMETRY TO STATISTICS — THE MATH, WITH ITS REFERENCES
An angle is a measurement; an estimate is a statement. Moving from one to the other honestly requires statistics. GTL does not present this layer as a private invention. It combines established statistical components, named here with their sources, and applies them to one specific object: the geometry of frozen price structures.
Volatility normalization. The σ in the ICS y-axis comes from the Yang-Zhang volatility estimator (Yang & Zhang, Journal of Business, 2000). It uses open, high, low and close data, including overnight, open-to-close and Rogers-Satchell-style range components. In GTL, this is what lets angles be measured in volatility-normalized space instead of raw price units.
Local probability. While a structure is alive, its current angle pair (θC, θF) is compared with archived breaks. Each historical break receives a Gaussian weight that decays with distance in angle space. This is a Gaussian KDE-style local weighting scheme. Its bandwidth follows Silverman's rule-of-thumb logic for two dimensions, h = σ̂ · n^(−1/6), recomputed from the chart's own history. Nothing is manually tuned.
Honest sample size. Weighted evidence can look larger than it really is: many tiny weights are not the same as many strong neighbors. GTL therefore uses the Kish effective sample size (Kish, Survey Sampling, 1965),
n_eff = (Σw)² / Σw²
to estimate how much effective evidence the weighted neighborhood actually contains.
Probability with humility. The weighted up/down vote is passed through a Beta(1,1) posterior, using n_eff as the effective evidence scale. The label only speaks when the posterior mean clears a one-sided 95% normal-approximation check against the 50/50 baseline. When that threshold is not met, the label does not force a call; it simply says the structure is too close to call.
Verification. The principle that probability forecasts must be scored against what actually happened goes back to Brier's 1950 paper in Monthly Weather Review, "Verification of Forecasts Expressed in Terms of Probability." In GTL, every estimate is graded when the break reveals the outcome.
Online calibration. Graded outcomes update fading-factor prequential counters, following the stream-learning evaluation framework of Gama, Sebastião and Rodrigues (Machine Learning, 2013). Fresh evidence receives more weight, while older evidence decays with λ = 0.999. The display can therefore show both the raw estimate and how estimates of the same kind have behaved on the current chart.
Stability. GTL also tracks estimate "jumpiness": the population standard deviation of the last five probability readings. The term and the general idea come from ensemble-forecast consistency research, especially Zsóter, Buizza and Richardson (Monthly Weather Review, 2009). GTL uses a chart-specific adaptation of that idea: a steady estimate and a choppy estimate are labeled differently, because a choppy estimate may still flip.
Nothing in this chain is exotic, and none of it is a performance guarantee. The original part is where the chain is pointed: at frozen structural geometry, measured inside a dimensionless coordinate space.
█ WHAT YOU SEE ON THE CHART
Frozen anchors. Two dashed horizontal lines mark the frozen HH and LL of the current structure, each with its exact level, and a dotted vertical line marks the anchor bar in the past where the freeze happened. These lines do not trail price — that is the whole point.
Geometric trend lines. Two solid lines run from the anchors to the live candle: ceiling from HH to the current high, floor from LL to the current low. They are the triangle hypotenuses. When the two lines converge, they stop at their intersection instead of crossing. The live θC and θF values sit as labels at the anchor.
Structure boxes. Every completed structure is archived as a box: one border color for structures that broke up, another for structures that broke down, and a dashed box for the structure still being built. How many past boxes you see is your choice.
Angle map. A table sorts the recent breaks by their break angles — ceiling side and floor side, each with direction and duration. An arrow row shows where the current live reading ranks among them, so you can literally see where "now" sits in the break history. The footer row carries the up/down estimate; once the calibration cell has enough samples, it shows two numbers, raw → calibrated.
Estimate label. A label floats ahead of the last candle and speaks in sentences: which direction the odds favor, what signals of this kind have actually done on this chart (or the estimated odds while calibration is still warming up), whether the signal is steady or choppy, and a living record — how many of the last 20 estimates were right. It only takes a side when the significance check passes; otherwise it says, honestly, that the structure is too close to call.
The pending phase. Between a break and the next freeze, preview anchors appear as dotted gray lines, the table shows an hourglass, and the estimate quietly switches to a second model trained on pending-phase angles to estimate the direction of the NEXT structure's break.
One disclosure that matters: on the live bar, angles and estimates can change until the candle closes. Everything the indicator learns from — and every alert it fires — reads confirmed bars only.
█ UNDER THE CHART — 29 EXPORTED COLUMNS
Everything drawn above is only a rendering. The numbers underneath are all exported to the Data Window, which means PulseWire's "Export chart data" hands you a complete CSV audit trail:
Live geometry & estimate, every bar:
Ceiling θ / Floor θ — the two live angles in ICS
Probability UP / Probability DOWN — the per-bar estimate (these two are also plots, so you can build threshold alerts on them directly)
Log Jump Bar — the stability (jumpiness) of the estimate
Log Cell Bar — which calibration cell this bar fell into
Structure snapshot, printed on every break bar:
Str Duration — how many bars the structure lived
Str Frozen HH / Str Frozen LL — the anchor levels
Str Max High / Str Min Low — the extremes reached inside
Str θ Ceil @Max / Str θ Floor @Min — the angles at those extremes
Str Break Dir — +1 up, −1 down
Estimate audit trail, on birth and break events:
Log Event — 1 = birth, 2 = break, 3 = both on one bar
Log θC Birth / Log θF Birth / Log P Birth / Log Sig Birth / Log nEff Birth — the forecast made the moment the structure was born
Log θC Pend / Log θF Pend / Log P Pend / Log Sig Pend / Log nEff Pend — the pending-phase forecast carried into this break
Log Hit Birth / Log Hit Pend — each forecast graded 1 or 0 against the actual break
Log Acc Birth / Log Acc Pend — the running accuracy of each estimate type
This is the same door the development study walked through. Export the CSV from your own chart, open it in a spreadsheet, in Python, or hand it to an AI assistant — and audit every sentence the label has ever told you.
█ SETTINGS THAT STAY OUT OF YOUR WAY
The settings menu is deliberately small: the lookback window, a few visual choices — colors, transparency, border style, table position, label size and offset, how many past boxes to show — and simple on/off toggles. That is the whole surface, because everything statistical is computed live from the chart itself: the KDE bandwidth from Silverman's rule, the effective sample size from Kish's formula, significance from the posterior, the calibrated rate from the fading counters, the pending-phase model switching in and out on its own. There is nothing to tune, and that is by design. The five documented constants from the development study are the only fixed numbers in the machine.
█ ALERTS
Three alerts cover the estimate's life cycle: Signal turns up, Signal turns down, and Signal gets choppy. Each fires once, on entering its state, and reads only confirmed bars — so what fired is what you will still see on the closed candle. For custom thresholds, Probability UP and Probability DOWN are exposed as plots: build Crossing Up or Greater Than alerts on them directly in PulseWire's alert dialog, at any level you like, as many as you like. Recommended frequency: Once Per Bar Close.
█ SEVENTEEN LANGUAGES
The angle map, the anchor labels and the estimate label speak 17 languages: English, Türkçe, Deutsch, Italiano, Français, Español, Bahasa Indonesia, Bahasa Melayu, Ελληνικά, Русский, 中文, 日本語, 한국어, हिन्दी, العربية, فارسی and עברית. Right-to-left scripts — Arabic, Persian, Hebrew — mirror the table layout automatically. One honest limitation: input settings and alert messages stay in English, because Pine requires compile-time constant strings there.
█ WHAT THIS IS — AND WHAT IT IS NOT
GTL is a research and structural analysis tool. It measures the geometry of frozen price structures, keeps honest statistics about its own estimates, and shows you both — the raw number and the track record, side by side. It is not a trading system, its estimates are not trade signals, and nothing in this script or this description is financial advice. The calibrated rates describe what has already happened on your chart's own history; they are not a promise about the next bar. On the live candle, readings can change until the close — confirmed statistics and learning update on closed bars only.
Read it the way it was built to be read: as an instrument standing on the shore, measuring the storm. Indicator
Universal Scalper SystemThe Universal Scalper System is a powerful technical indicator designed specifically for intraday scalping on lower timeframes like 1-minute and 5-minute charts. It provides a streamlined approach to trading by combining trend identification with essential market data.
Key Features:
9 EMA Crossover: Generates clear, actionable Buy and Sell signals the moment the price crosses and closes beyond the 9-period Exponential Moving Average (EMA).
Live Market Dashboard: Includes a fully customizable dashboard that displays:
Current Chart Timer: Countdown until the current candle closes.
15-Minute Timeframe Timer: Tracks the closure of the 15-minute candle for higher-timeframe context.
Real-time Candle Info: Shows if the current candle is Bullish or Bearish along with live volume data.
Highly Customizable: Traders can easily adjust EMA settings, dashboard colors, text sizes, and dashboard positioning directly through the settings panel to fit their unique workspace.
Built-in Alerts: Features integrated alert conditions for both Buy and Sell signals, ensuring you never miss a trading opportunity.
This system is perfect for traders who prioritize speed, clean visuals, and real-time data at their fingertips.
Tags: Scalping, EMA, CrossOver, Dashboard, TradingSystem, PriceAction, TechnicalAnalysis, Indicator, Scalper, LiveTimer Indicator
AUTO TRENDLINE PROauto trendline pro
auto trendline pro is an automatic trendline indicator designed to display multiple degrees of market structure at the same time: live trendlines, confirmed trendlines, and higher timeframe trendlines.
the purpose of the tool is to help traders identify dynamic support and resistance lines, projected levels, confirmed breaks, and higher timeframe structure directly on the chart.
the indicator uses pivot points, wick or body anchors, atr-based validation, touch detection, duplicate filtering, forward projection, optional channels, and a dashboard for fast market reading.
it can be used for scalping, intraday trading, swing trading, and macro analysis depending on the selected settings.
---
inputs guide
degrees
live degree
enables live trendlines. this mode reacts faster to recent price action, but it can repaint because the pivots are still developing. it is useful for short-term market reading and early structure detection.
confirmed degree
enables confirmed trendlines. this mode is more stable because it uses confirmed pivots. it is recommended for cleaner analysis and more reliable structural levels.
htf degree
enables higher timeframe trendlines. this mode brings larger market structure into the current chart and helps identify major dynamic support and resistance levels.
anchor source
selects how the trendline anchors are calculated.
wick uses candle highs and lows.
body uses candle open and close extremes.
wick is more aggressive and reacts to full price extremes. body is cleaner and can reduce noise.
---
pivot strength
live pivot l/r
controls the strength of live pivots. a lower value creates more reactive trendlines. a higher value creates fewer but cleaner lines.
confirmed pivot l/r
controls the strength of confirmed pivots. a higher value makes the confirmed trendlines more selective and more structural.
htf pivot l/r
controls the pivot strength used on the higher timeframe. higher values create more macro-level lines.
---
htf source
htf timeframe
selects the higher timeframe used for htf trendlines. examples: 4h, 1d, 1w. higher timeframes provide stronger macro structure.
htf ath/atl window
defines the lookback window used to detect higher timeframe highs and lows. a larger value allows the indicator to anchor lines to more important historical extremes.
anchor htf line at ath / atl
allows htf lines to be anchored from the highest high or lowest low inside the selected htf window. this is useful for long-term trendlines and cycle analysis.
htf compute in log space
calculates htf trendlines using logarithmic logic. this is useful for assets with large percentage moves, such as crypto, because it gives a more balanced macro structure.
---
structure and validation
lines per side chart degrees
defines how many chart-degree lines are displayed per side. increasing this value shows more trendlines but can make the chart busier.
lines per side htf
defines how many higher timeframe lines are displayed per side. a lower value keeps the chart cleaner. a higher value gives more macro context.
new-anchor candidates
defines how many recent pivots are tested as possible new anchors. higher values test more combinations.
older-anchor window
defines how many older pivots can be used with a recent pivot to create a valid trendline.
min bars between anchors
defines the minimum distance between two trendline anchors. a low value creates shorter lines. a higher value creates more meaningful structural lines.
allowed pierces
defines how many times price is allowed to pierce a line during validation. zero means strict validation.
pierce tolerance atr
defines the atr-based tolerance used when checking if price has pierced a line. a lower value is stricter. a higher value allows more flexibility.
touch tolerance atr
defines the atr-based tolerance used to count touches on a trendline. a higher value detects more touches. a lower value keeps only precise touches.
dedupe distance atr
filters trendlines that are too close to each other. a higher value removes more duplicate lines.
max validation span
defines the maximum number of bars used when validating a trendline. this prevents the indicator from validating lines across an excessive historical distance.
---
channels, break and extension
show channels
enables channels around the dominant trendline. channels help visualize the reaction area around a trendline instead of focusing only on a single line.
break = n consecutive closes beyond
defines how many consecutive candle closes are required to confirm a break. a value of 1 is faster. a value of 2 or more is stricter.
forward projection bars
defines how far the trendlines are projected into the future.
infinite extension
extends the lines continuously to the right. this is useful when using trendlines as ongoing dynamic support and resistance.
---
display
price projection label
shows the projected price at the end of a trendline. this helps identify the current reaction level quickly.
show trendline labels
enables or disables labels on trendlines. keeping this off gives a cleaner chart.
strength rating
shows a visual strength rating based on the number of valid touches. more touches generally mean a more important line.
show dashboard
enables the dashboard. the dashboard summarizes confirmed support, confirmed resistance, htf support, htf resistance, htf extremes, and validation status.
dashboard position
selects the position of the dashboard on the chart.
---
aesthetics
support
sets the color of support trendlines.
resistance
sets the color of resistance trendlines.
htf glow / accent
sets the accent color used for higher timeframe emphasis.
broken
sets the color used when a trendline is broken.
atr length
defines the atr length used for tolerances, validation, touch detection, break detection, and duplicate filtering.
---
how to use the indicator
start by using confirmed degree and htf degree. these two modes give the cleanest structure.
live degree is useful for faster market reading, but beginners should understand that live pivots can repaint while they are forming.
support lines are usually below price and can act as dynamic reaction zones.
resistance lines are usually above price and can act as dynamic rejection zones.
when price approaches a confirmed or htf trendline, watch how it reacts. price can reject the line, break through it, or compress near it before a stronger move.
a break is cleaner when price closes beyond the line. this is why the break confirmation input is important.
---
beginner tutorial
1. choose your trading timeframe, such as 15m, 1h, 4h, or 1d.
2. enable confirmed degree to display stable trendlines.
3. enable htf degree to display higher timeframe structure.
4. keep live degree enabled only if you want more reactive lines.
5. wait for price to approach a support or resistance trendline.
6. observe the candle reaction near the line.
7. a rejection can indicate that the line is still respected.
8. a confirmed close beyond the line can indicate a structural break.
9. use the dashboard to monitor the main confirmed and htf levels.
10. never use a trendline alone as a full trade signal. combine it with market structure, volume, candles, liquidity, and risk management.
---
simple beginner setup
live degree: off
confirmed degree: on
htf degree: on
anchor source: wick
confirmed pivot l/r: 10
htf pivot l/r: 8
allowed pierces: 0
break = n consecutive closes beyond: 2
show channels: on
show trendline labels: off
show dashboard: on
this setup keeps the chart clean and focuses on confirmed structure.
---
scalping setup
live degree: on
confirmed degree: on
htf degree: on
live pivot l/r: 3 to 5
confirmed pivot l/r: 8 to 12
break = n consecutive closes beyond: 1 to 2
forward projection bars: 10 to 30
show trendline labels: off
this setup gives faster signals and more reactive structure, but it should be used with more caution.
---
swing trading setup
live degree: off
confirmed degree: on
htf degree: on
confirmed pivot l/r: 10 to 20
htf pivot l/r: 8 to 15
htf timeframe: 1d or 1w
htf compute in log space: on for crypto
break = n consecutive closes beyond: 2 or 3
infinite extension: on
this setup focuses on larger trendlines and reduces short-term noise.
---
dashboard guide
conf resist
shows the main confirmed resistance trendline level.
conf support
shows the main confirmed support trendline level.
htf resist
shows the main higher timeframe resistance trendline level.
htf support
shows the main higher timeframe support trendline level.
htf ath / atl
shows the higher timeframe extreme levels used for macro context.
validation
shows that the lines are built using structure and validation logic.
---
important notes
a trendline is not an automatic buy or sell signal.
a trendline is a decision zone.
the more clean touches a line has, the more important it becomes.
a close beyond a line is usually more important than a wick through the line.
higher timeframe lines should always be respected because they represent larger market structure.
this tool is designed to organize chart structure, but risk management remains essential.
Indicator
Hurst Regime Sentinel [JOAT]HURST REGIME SENTINEL
A proper R/S Hurst-exponent regime classifier — the single most respected statistical test for "is this market trending, mean-reverting, or random?". On top of the textbook R/S analysis, the Sentinel adds a five-class regime taxonomy (Strong MR, MR, Random, Trend, Strong Trend), a confirmation-bars filter to suppress flicker, a right-side floating Hurst badge, a regime-tinted background, and — uniquely — a Suggested JOAT Indicator dashboard row that names the best-fit companion script in the JOAT suite for the current regime.
The Hurst exponent, properly
The Hurst exponent H is a number between 0 and 1 that characterises the long-run persistence of a time series:
H < 0.5 — anti-persistent / mean-reverting. The series tends to reverse its recent direction.
H = 0.5 — random walk (Brownian motion). No memory.
H > 0.5 — persistent / trending. The series tends to continue its recent direction.
The classical estimator is R/S analysis (rescaled range): split the window into sub-segments, compute the range of cumulative deviations from each sub-mean, normalise by the sub-stdev, average, and fit a log-log slope. This script implements that estimator over a configurable lookback (default 100, the canonical value), with optional log-return source for theoretical correctness, and an EMA smoother on top of the raw H series to give a stable regime read.
Five-class regime taxonomy
The Sentinel does not just classify into trend/MR/random — it sub-classifies the trend and MR sides:
Strong MR — H below the strong-MR boundary (default 0.30). Severely anti-persistent. Aggressive reversion regime.
MR — H between strong-MR and the MR upper (default 0.40). Mean-reverting.
Random — H between MR upper and trend lower (default 0.55). No statistical edge from persistence assumptions.
Trend — H above trend lower. Trending.
Strong Trend — H above the strong-trend boundary (default 0.65). Strongly persistent. Aggressive momentum regime.
A Minimum-bars-to-confirm filter (default 3 bars) suppresses regime flicker; a change must persist this many bars before it is committed.
Suggested JOAT Indicator row (unique)
The dashboard exposes a Suggested Indicator row that names the best-fit companion script from the JOAT suite for the current regime. The user can pick which suggestions appear (defaults: Volatility Reversion Bands Pro for MR, Quantum Trend Matrix for Trend, Liquidity Magnet Pro for Random — but every other JOAT indicator is selectable). This converts the abstract regime read into a concrete next action: when the regime changes, the script tells you which other tool in the suite to put on the chart.
Visual system
Right-side floating label — anchored N bars to the right of the latest bar with current H value, regime, and sub-class.
Regime-change labels — drawn at the bar where a confirmed regime change occurs.
Background tint by regime — violet for MR, teal for Trend, untinted for Random. Strong sub-classes use a stronger (lower-transparency) alpha than mild sub-classes. Both alphas are configurable.
Optional Hurst line companion — when enabled, plots the H series scaled to a configurable fraction of the visible price range. Use to visually track H movement over time. Off by default for a clean chart.
Optional reference levels at 0.40 / 0.50 / 0.55 when the line is shown.
A locked Mystic palette (teal trend / violet MR / white random on a midnight-blue ground) gives the chart a distinctive structural identity.
Dashboard
Monospaced table positionable to any of nine corners. Surfaces:
Current H value (raw and smoothed).
Regime classification with glyph.
Sub-class (Strong MR / MR / Random / Trend / Strong Trend).
Bars in current regime.
Distance from H to nearest threshold.
Suggested JOAT Indicator row (toggleable).
Source series in use (Close / HL2 / HLC3 / OHLC4 / Log Returns).
Alerts
Multiple alert conditions, each independently controllable:
Regime changed to MR / Random / Trend
Sub-class changed to Strong MR / Strong Trend
H crosses 0.50 (random-walk centre)
How to read it
Three reads, in order of conviction:
Sub-class entry (Strong MR or Strong Trend) — the highest-conviction read. The market has decisively committed to a persistence regime; the suggested companion indicator becomes high-conviction.
Regime change confirmed (after the minimum-bars filter) — meaningful enough to switch toolkits. If you were trading momentum and the script now reads MR, your edge has just rotated.
H crossing 0.50 — the structural fault line. Above, persistence is positive; below, it is negative. Even without a sub-class entry, a clean cross of 0.50 is a regime warning.
Suggested settings
Defaults (lookback 100, EMA smoothing 14, MR upper 0.40, trend lower 0.55, strong boundaries 0.30 / 0.65) are tuned for daily and 4H charts on liquid markets — the timeframes where R/S analysis is statistically most meaningful. For 1H and below the indicator works but the H estimate becomes noisier; raise the EMA smoother to compensate. For very long horizons (1W+) increase lookback to 200.
Originality / what's reused
The R/S Hurst estimator is the textbook 1951 method — public-domain statistics, implemented from the original Hurst paper. The implementation here — the bounded-loop R/S computation with sub-segment averaging, the five-class regime taxonomy with strong sub-classes, the confirmation-bars regime-change filter, the regime-driven background tint with mild/strong alpha tiers, the optional scaled Hurst-line overlay, the right-side floating badge, and the suggested-JOAT-indicator dashboard row — is JOAT-original. No third-party code reused.
Open source
Published open-source under the default Mozilla Public License 2.0. The R/S loop, the regime classifier, the suggested-indicator router, and the dashboard are isolated modules. Forks welcome with credit.
Limitations
Hurst R/S is statistical — it describes the recent past, it does not predict the future. The estimator carries the natural noise of finite-sample R/S; the EMA smoother is there to suppress flicker but cannot eliminate underlying noise on short lookbacks. The "Suggested JOAT Indicator" row is a heuristic mapping from regime to tool, not a prediction that any specific signal from that tool will fire — it tells you which corner of the toolkit to look at; the tool itself tells you when to act.
—
-made with passion by jackofalltrades
Indicator
Indicator
Multi-TimeFrame Multi-Indicator Dashboard🚀 Multi-Timeframe Multi-Indicator Market Structure Dashboard
🟢 Overview
The **Multi-Timeframe Multi-Indicator Dashboard** is an all-in-one market scanner designed to give traders an immediate, high-level view of an asset's trend across multiple layers of time. Instead of constantly flipping between charts or cluttering your workspace with dozens of indicators, this script compiles key moving averages, momentum oscillators, and volatility indicators into a single, highly readable table directly on your primary workspace.
This tool is optimized for **Equities, Forex, Crypto, Indices, and Commodities traders** who rely on multi-timeframe confluence to confirm high-probability trade setups and eliminate analysis paralysis.
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🛠️ Key Features
**Multi-Timeframe Confluence Matrix:** Instantly track market structure across 6 default timeframes: **5M, 15M, 1H, Daily, Weekly, and Monthly**.
**8 Integrated Technical Metrics:**
**Trend Identification:** SMA 9, SMA 20, SMA 50, SMA 100, and SMA 200.
**Momentum & Volatility:** Relative Strength Index (RSI 50-line crossover), MACD Histogram (bullish/bearish momentum shifts), and SuperTrend.
**Fully Customizable Layout:** Toggle specific timeframes or indicators on/off via the user inputs menu to perfectly match your trading style. You can also change the table position (e.g., top-right, bottom-left) and text size.
**Smart Alert Engine:** Configure the script to send real-time alerts the exact moment an indicator shifts states (Bullish $\leftrightarrow$ Bearish) on your primary timeframes.
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🎛️ Settings & Customization
1. **Dashboard Display:** Control the visibility, positioning anchor (top-right, bottom-right, top-left, bottom-left, middle-right, middle-left), and text scaling of the canvas table.
2. **Timeframes to Display:** Toggle individual columns to focus strictly on scalping or macro swing horizons.
3. **Indicators to Display:** Strip out unnecessary lines to match your personal strategy components.
4. **SuperTrend Settings:** Manually adjust the ATR Length and Multiplier inputs for tighter or wider trend bands.
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📝 Disclaimer
This indicator is built purely for analytical visualization and informational purposes. It does not constitute financial advice. Always practice strict risk management and combine dashboard confirmation with your own broader trading plan. Indicator
Event HorizonEvent Horizon is a historical analog projection fan designed to answer one practical question:
What has price tended to do after market conditions similar to the current one?
Instead of using a fixed crossover, oscillator threshold, or trend flip, this indicator builds a market fingerprint from the current chart, searches historical bars for similar conditions, and projects how those past analogs moved forward. The result is a visual forward fan showing possible path behavior, consensus direction, dispersion, confidence, and the closest historical analog path.
The goal is not to predict the future with certainty. The goal is to give traders a structured way to compare the current setup against similar historical environments and quickly see whether the analogs are aligned, scattered, bullish, bearish, or not useful.
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What makes this script different
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Most projection tools draw a channel, regression, moving average extension, or volatility cone from a fixed formula.
Event Horizon uses a historical analog engine. Each bar is converted into a multi-factor feature profile, then compared against prior market states using weighted Euclidean similarity. The closest historical analogs are used to create a forward projection fan.
The script combines:
• Historical analog matching
• Weighted Euclidean distance
• Regime-aware scoring
• Volatility and trend-state filtering
• Consensus projection logic
• Closest historical path overlay
• Agreement and confidence scoring
• Directional historical event dots
• A visual fan that shows uncertainty instead of one hard prediction
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How it works
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1. Market fingerprint
The script measures the current market using multiple dimensions, including:
• Recent price movement
• Trend slope
• ATR expansion and compression
• Candle range and body behavior
• Wick imbalance
• Position relative to recent structure
• Breakout distance
• Volume ratio and volume trend
• ATR percentile
• ADX / trend strength
• Historical shape samples
This creates a multi-dimensional profile of the current setup.
2. Historical analog search
The current profile is compared to historical profiles on the same chart. Similarity is calculated with weighted Euclidean distance, so higher-value features such as trend, volatility regime, and price-shape behavior can matter more than smaller candle details.
Closer historical examples receive stronger match scores.
3. Regime awareness
The script also classifies the current environment into regimes such as trend, compression, volatility expansion, volume shock, or range/chop. Historical examples from incompatible regimes are penalized, helping reduce weak comparisons.
4. Forward projection
Once the best analogs are selected, the script looks at what actually happened after those historical setups. Those forward moves are normalized and projected from the current anchor point.
5. Consensus and confidence
The indicator summarizes the analog group with:
• Directional bias
• Agreement percentage
• Dispersion
• Confidence score
• Edge state: TRADEABLE, CAUTION, or NO EDGE
• Historical self-test statistics
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How to read the fan
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The colored fan shows the projected analog field.
The colored median shows the consensus path of the analog set.
The white line shows the closest visible historical analog path. It is not a guaranteed target. It is the path taken by the most similar past setup selected by the engine.
The wider the fan, the more disagreement there is between analogs.
The tighter the fan, the more historically aligned the analogs are.
The confidence and edge label are important. A bullish-looking fan with low confidence or high dispersion should be treated differently than a bullish fan with strong agreement and cleaner regime structure.
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Historical dots
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Historical event dots help visually review where prior projection events occurred.
• Bullish projection dots appear below price
• Bearish projection dots appear above price
• Mixed or neutral readings are visually separated
This makes it easier to inspect whether the indicator has been identifying useful directional conditions on the current symbol and timeframe.
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How to use it
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For newer traders:
1. Start on the Daily or 4H chart.
2. Look at the colored median.
3. Check whether the white analog path agrees with the median.
4. Check confidence and agreement.
5. Avoid forcing trades when the label says NO EDGE or when dispersion is high.
A stronger bullish read usually has:
• Median path rising
• White analog path also rising
• Agreement above roughly 65%
• Confidence above roughly 70
• Low or medium dispersion
• Edge state showing TRADEABLE or CAUTION, not NO EDGE
A weaker or avoidable read usually has:
• Median and white path disagreeing
• Agreement near 50%
• High dispersion
• Low confidence
• Range/chop regime
• NO EDGE label
For experienced traders:
Use the fan as an analog-based context layer. It is most useful when combined with your own structure, liquidity, trend, support/resistance, volume, or macro view. The script is designed to show whether historical analog behavior supports or conflicts with the trade idea you already see on the chart.
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Suggested settings
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Balanced stocks / ETFs:
• Mode: Current Bar Projection
• Visual Mode: Cinematic
• Fan Style: Hybrid Swarm + Contours
• Horizon: 30
• Memory Lookback: 1800
• Max Analogs: 30
• Minimum Analogs: 6
• Pre-Event Window: 20
• Shape Samples: 6
• Path Scale: 1.0
Crypto:
• Horizon: 24
• Memory Lookback: 2000 to 2500
• Path Scale: 0.75 to 0.90
• Flexible direction matching
Intraday:
• Horizon: 20 to 24
• Minimum Analogs: 8
• Path Scale: 0.75 to 1.0
• Use liquid symbols only
Trend continuation:
• Direction Matching: Strict
• Mirror Opposite Direction: Off
• Path Scale: 1.0
Reversal / exhaustion:
• Direction Matching: Flexible
• Mirror Opposite Direction: On
• Path Scale: 0.75
• Shorter horizon preferred
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Best use cases
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Event Horizon is best suited for:
• Liquid stocks
• Major ETFs
• Index products
• Major crypto pairs
• Trend continuation setups
• Post-compression expansion
• Structure breaks
• Swing-trade context
• Daily and 4H analysis
It is less suitable for:
• Illiquid symbols
• Very new tickers with limited history
• Low-volume penny stocks
• Earnings gaps
• Binary news events
• Extremely short scalping timeframes
• Markets with sudden one-off catalysts
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Important notes
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This is an analog projection tool, not a standalone buy/sell system.
Historical similarity does not guarantee future behavior. Market structure, liquidity, volatility, news, and macro conditions can change quickly. The fan should be used as a decision-support layer, not as a guaranteed forecast.
The strongest readings occur when the median, white analog path, agreement, confidence, and regime state all point in the same direction.
The weakest readings occur when analogs are scattered, confidence is low, dispersion is high, or the script identifies a no-edge environment.
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Summary
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Event Horizon turns historical market behavior into a forward analog projection fan.
It helps traders see:
• What similar past setups did next
• Whether those analogs agree or disagree
• Whether the current regime supports the projection
• Whether the projected path is tight or scattered
• Whether the setup has enough confidence to matter
Use it to add historical context, probability awareness, and regime-based discipline to your chart analysis.
Indicator
Volatility Regime Compass [JOAT]Volatility Regime Compass
Introduction
Volatility Regime Compass is an open-source volatility state classifier that continuously measures where current ATR stands relative to its own historical distribution and maps it to one of four named regimes: Compressed, Normal, Elevated, and Extreme. The classification is not binary (high or low) — it uses a rolling percentile ranking against configurable lookback windows so the regime reflects where current volatility stands within its recent history, not against a fixed absolute threshold that becomes stale as market conditions evolve.
The practical value is in strategy switching: mean-reversion techniques tend to work in compressed regimes, breakout and momentum techniques in elevated ones. Knowing which regime is active before selecting a technique reduces category errors that produce losses.
Core Concepts
1. ATR Percentile Ranking
Rather than comparing ATR to a static multiplier, the indicator ranks the current ATR value within a rolling distribution of historical ATR values. This produces a percentile score from 0 to 100 that is self-normalizing across different instruments and timeframes:
float atrHi = ta.highest(atrVal, i_rankLen)
float atrLo = ta.lowest (atrVal, i_rankLen)
float atrPct = (atrHi - atrLo) > 0 ?
(atrVal - atrLo) / (atrHi - atrLo) * 100.0 : 50.0
A reading of 80 means current ATR is in the 80th percentile of its recent range — clearly elevated. A reading of 15 means ATR is near multi-period lows — compressed.
2. Four-State Regime Classification
The percentile score maps to four regimes with configurable boundary thresholds. Defaults are: Compressed (below 25th percentile), Normal (25th to 60th), Elevated (60th to 85th), Extreme (above 85th). Crossing a regime boundary triggers a transition event labeled on the chart.
3. Multi-Band Visualization
Five ATR bands project above and below close at configurable multiples (0.5×, 1×, 1.5×, 2×, 2.5× ATR). Each band is color-coded by regime — tighter bands in compressed regimes shade cooler, wider bands in extreme regimes shade hotter using a 5-stop gradient. This gives instant visual calibration of price's relationship to current volatility structure.
4. Volatility Trend
The rate of change of ATR is computed and smoothed. Positive volatility trend (ATR rising) is labeled differently from negative trend (ATR contracting). This distinguishes a currently-elevated but contracting regime from one that is expanding — the former is more likely to produce consolidation, the latter continuation.
Features
ATR percentile ranking: Self-normalizing volatility score relative to recent history
Four volatility regimes: Compressed, Normal, Elevated, Extreme with configurable boundaries
Regime transition labels: On-chart labels at every regime change event
Five ATR expansion bands: Projected above and below close, gradient-colored by regime
Volatility trend direction: Rising vs contracting ATR tracked independently of level
Candle coloring: Candles reflect current volatility regime in real time
Regime background shading: Chart background tint corresponds to current regime
Dashboard: Current ATR, percentile, regime, trend direction, and band levels
Input Parameters
ATR Settings:
ATR Period: ATR calculation length (default: 14)
Percentile Lookback: Rolling window for ATR percentile ranking (default: 100)
Regime Thresholds:
Compressed Below: Percentile below which regime is Compressed (default: 25)
Elevated Above: Percentile above which regime is Elevated (default: 60)
Extreme Above: Percentile above which regime is Extreme (default: 85)
How to Use This Indicator
Step 1: Check the Current Regime
Read the REGIME row in the dashboard. This tells you whether to expect range-bound or trending behavior in the near term.
Step 2: Watch for Regime Transitions
A transition from Compressed to Elevated is the setup for breakout strategies. A transition from Extreme back toward Normal may signal trend exhaustion.
Step 3: Use Bands as Structural Reference
The ATR bands define statistically reasonable price excursion limits for the current volatility state. Closes beyond the 2× or 2.5× band while in a Compressed regime are structurally significant events.
Step 4: Combine with Directional Indicators
This indicator classifies volatility magnitude, not direction. Pair it with a trend or momentum tool to apply regime context to directional decisions.
Indicator Limitations
Percentile ranking depends on lookback length; very short lookbacks can produce unstable regime classifications during sudden volatility spikes
The four-state classification is a simplification; volatility is continuous and regime boundaries are heuristic
Volatility expansion does not indicate direction — it only measures magnitude of movement
Originality Statement
The combination of a self-normalizing ATR percentile ranking, a four-state regime classifier with configurable percentile boundaries, gradient-coded multi-band projection, and a simultaneous volatility trend tracker in a single Pine Script v6 publication constitutes the original contribution. Standard ATR indicators display the raw value or a fixed-multiple band without regime classification or percentile normalization.
Disclaimer
This indicator is provided for educational and informational purposes only. It is not financial advice. Volatility regime classifications are statistical summaries of historical data and do not predict future price movement. Trading involves substantial risk of loss.
-Made with passion by jackofalltrades
Indicator
Kalman Trend Filter [JOAT]Kalman Trend Filter
Introduction
Kalman Trend Filter is an open-source trend detection indicator that applies a two-state Kalman filter to price, tracking both the filtered price level and its velocity simultaneously. Unlike exponential moving averages — which apply a fixed exponential decay to past data — the Kalman filter dynamically adjusts its responsiveness based on the ratio of process noise to measurement noise. When price is moving consistently in one direction, the filter trusts new measurements more heavily. When price is noisy, it trusts its own model more heavily.
The practical result is a trend line that responds faster than an equivalent EMA during genuine trends while remaining smoother during chop. The velocity state is the direct indicator of trend direction and strength — it is what drives signal generation and candle coloring.
Core Concepts
1. Two-State Kalman Filter
The filter tracks two quantities: price (position state) and the rate at which price is changing (velocity state). The prediction step projects both states forward using simple kinematic equations. The correction step updates them based on how much the current close deviates from prediction:
// Prediction
float xPred = xEst + vEst
float pPred = pEst + qNoise
// Kalman gain
float kGain = pPred / (pPred + rNoise)
// Correction
float xEst = xPred + kGain * (close - xPred)
float vEst = vEst + kGain * (close - xPred)
The process noise (qNoise) and measurement noise (rNoise) parameters control how much the filter trusts its own momentum model versus new price data.
2. Velocity as Trend Proxy
The velocity state is the most analytically useful output. Positive velocity means the filtered price is accelerating upward; negative means downward. The magnitude of velocity indicates trend strength. Velocity crossing zero is a higher-quality trend reversal signal than a moving average crossover because it reflects the momentum of the filtered series, not the level.
3. Gradient Candle Coloring
Candles are painted using a two-sided gradient driven by the velocity state. Strongly positive velocity produces bright cyan candles; strongly negative produces bright magenta. Near-zero velocity transitions to neutral. The gradient intensity scales with velocity magnitude rather than applying a binary color switch.
4. Velocity Oscillator
The velocity state is plotted as a separate sub-indicator below the main chart, providing a visual oscillator that crosses zero at trend reversals. Unlike momentum oscillators derived from price differences, this oscillator represents the Kalman filter's internal estimate of trend rate — it is inherently smooth without additional EMA smoothing.
Features
Two-state Kalman filter: Tracks price level and velocity simultaneously
Configurable noise parameters: Process and measurement noise control filter responsiveness
Filtered price line overlay: Smooth trend line drawn on the price chart
Velocity oscillator: Kalman velocity state as a zero-line oscillator
Velocity zero-cross signals: Bull and bear signals when velocity crosses zero
Gradient candle coloring: Cyan for upward velocity, magenta for downward, scaled by magnitude
Dashboard: Current filtered price, velocity, trend state, and noise parameters
Alerts: Velocity zero-cross and extreme velocity alerts
Input Parameters
Kalman Engine:
Process Noise (Q): How much the filter trusts its own velocity model (default: 0.01)
Measurement Noise (R): How much the filter trusts new price measurements (default: 1.0)
Initial Velocity: Starting velocity state (default: 0.0)
Display:
Show Filter Line toggle
Show Velocity Oscillator toggle
Show Candle Color toggle
How to Use This Indicator
Step 1: Read Velocity Direction
Positive velocity (oscillator above zero, cyan candles) indicates the filter is trending upward. Negative velocity (below zero, magenta candles) indicates downward trend. The magnitude tells you how strong.
Step 2: Use Velocity Zero-Cross as Trend Change Signal
When velocity crosses from negative to positive, the filter's internal momentum model has flipped bullish. This is more reliable than a price crossover because it reflects the rate of change of the filtered series.
Step 3: Tune Noise Parameters to Timeframe
On faster timeframes, increase Q slightly (0.02–0.05) to make the filter more responsive. On weekly charts, reduce Q (0.001–0.005) for a smoother, slower-adjusting filter.
Step 4: Combine with Regime Context
The Kalman filter performs best in trending regimes. Combine with Fractal Dimension Oscillator: when FDO shows a trending regime, Kalman velocity direction provides the trend bias.
Indicator Limitations
The Kalman filter assumes a linear motion model; non-linear price dynamics (sudden gaps, news events) produce temporary distortion in the filter state
Optimal Q and R values are instrument and timeframe dependent; no universal setting works everywhere
Velocity zero-crosses during low-volatility consolidation can produce frequent false signals
Originality Statement
The two-state Kalman filter implementation combined with a velocity-driven gradient candle coloring system, a dedicated velocity oscillator, and dual-input noise parameter configuration in a single publication is the original contribution here. Most published Kalman filter scripts on PulseWire implement a single-state position filter with no velocity tracking and no gradient visualization.
Disclaimer
This indicator is provided for educational and informational purposes only. It is not financial advice. Kalman filter outputs are mathematical estimates based on prior observations and do not predict future price. Trading involves substantial risk of loss.
-Made with passion by jackofalltrades
Indicator
Entropic Structure Bands [JOAT]Entropic Structure Bands
Introduction
Entropic Structure Bands is an open-source overlay indicator that dynamically selects the best-fitting Ordinary Least Squares regression window from recent structural pivots and surrounds that regression channel with entropy-adjusted deviation bands. The key innovation over standard regression channel indicators is twofold: the window length is selected optimally each bar by searching through available pivot anchors for the highest R² × log(N) quality score, and the band width is modulated by the current Shannon entropy of log returns — widening during chaotic periods and tightening during orderly ones.
Core Concepts
1. Optimal Regression Window Search
Rather than using a fixed lookback, the indicator records the bar index of every confirmed pivot high and low. Each bar, it tests several candidate windows anchored at recent pivots and selects the one that maximizes a performance score: R² multiplied by the natural log of the window length. This rewards both fit quality and window depth simultaneously:
float score = r2 * math.log(float(N))
// highest score wins; window updates every bar
if trial.perfScore > bestScore
bestScore := trial.perfScore
bestMdl := trial
The regression channel therefore adapts to where significant price structure has occurred, not to an arbitrary fixed period.
2. Shannon Entropy Modulation
Shannon entropy of the log return distribution is computed using a histogram-binning approach. Low entropy means returns are concentrated — price is moving in an organized, directional way. High entropy means returns are evenly distributed — chaotic, noisy conditions. Band width scales with entropy:
float entAdjDev = bestMdl.stdErr * (1.0 + entNorm * 0.8)
When entropy is low (below the configurable threshold), the market is classified as orderly and signals are enabled. This prevents signals from firing into chaotic conditions where regression bands have less predictive value.
3. Trend-Confluence Signal Logic
Signals require simultaneous alignment of six conditions: regression slope direction, price position relative to midline, recent pullback to the inner band, momentum confirmation, optional HTF slope alignment, optional ADX trending gate, and optional RSI gate. Each condition is individually toggleable. This multi-factor gate replaces simple band-crossover logic with a structured confluence requirement.
4. Forward Projection
The regression channel extends forward by a configurable number of bars beyond the right edge of the chart. A projection target label marks the estimated price at the end of the projection window based on the current slope and intercept. This gives visual context for where the regression model expects price to be if the current trend continues.
5. Z-Score Candle Coloring
Each candle's position within the channel is expressed as a Z-score (standard deviations from the regression midline). Candles far above the midline (overbought extension) are tinted bear-color; candles far below (oversold extension) are tinted bull-color. This provides immediate visual context for where price stands within its current regression structure.
Features
Dynamic regression window: Optimal window selected each bar from pivot anchor scan
R² quality gate: Configurable minimum R² prevents low-fit windows from being used
Entropy-adjusted bands: Band width scales with Shannon entropy of log returns
Multi-factor signal gate: Six independently configurable confluence conditions
Forward projection: Channel extended beyond right edge with target label
Z-score candle coloring: Candles painted by standard deviation position in channel
Inner and outer bands (±1σ, ±2σ): Gradient-filled channel layers
Glow-effect midline: Double-drawn center line with transparency for depth
10-row dashboard: R², entropy, Z-score, duration, HTF alignment, ADX, RSI, signal state
JSON webhook alerts: Alert messages formatted as JSON with EP, TP, SL, and R²
Input Parameters
Regression Engine:
Pivot Scan Horizon: Number of pivots to evaluate as regression anchors (default: 20)
Pivot Sensitivity: Left/right bars for pivot confirmation (default: 5)
Min R² Quality Gate: Minimum fit quality to use a window (default: 0.50)
Band Multiplier 1/2: Inner and outer band standard deviation multiples (default: 1.0, 2.0)
Entropy System:
Entropy Lookback: Bars for entropy calculation (default: 20)
Entropy Bins: Histogram bins for return distribution (default: 10)
Low Entropy Threshold: Threshold below which market is classified as orderly (default: 2.5)
How to Use This Indicator
Step 1: Read the Slope Bias
Check the dashboard's Slope Bias row. BULLISH or BEARISH indicates the current regression direction. This is the primary directional input.
Step 2: Check Entropy State
LOW (orderly) entropy is the condition under which signals are most reliable. HIGH entropy warns that the regression model is operating in a chaotic environment.
Step 3: Wait for Signal Labels
LONG and SHORT labels appear only when the full confluence gate is satisfied. Each label shows entry price, TP1, TP2, stop loss, and R² quality.
Indicator Limitations
Regression channels repaint historically when the optimal window shifts to a new anchor; use the confirmed-bar signals for non-repainting entry logic
In markets with very few pivots, the scan horizon may find suboptimal windows with low R²
Shannon entropy requires sufficient lookback to produce stable estimates
Originality Statement
The dynamic pivot-anchored regression window search using R² × log(N) scoring, combined with Shannon entropy-modulated band width and a six-condition confluence signal gate, is the original analytical architecture of this publication. No existing published Pine Script regression channel indicator implements adaptive window selection from pivot anchors with entropy modulation in this manner.
Disclaimer
This indicator is provided for educational and informational purposes only. It is not financial advice. Regression channels are mathematical models of past price behavior and do not predict future price. Trading involves substantial risk of loss.
-Made with passion by jackofalltrades
Indicator
Machine Learning: Volume-Weighted Mean Reversion [Dots3Red]█ MACHINE LEARNING: VOLUME-WEIGHTED MEARN REVERSION KERNEL REGRESSION
Nadaraya-Watson kernel regression is a non-parametric machine learning method. Unlike moving averages which apply fixed, predefined weights to historical bars, kernel regression derives each bar's weight from a mathematical function — the kernel — that measures how relevant that bar is to the current estimate. No hardcoded coefficients. No assumed shape. The model adapts purely from the data.
This script introduces a fundamental extension to the standard method: volume as a second weighting dimension . The result is a regression curve that gravitates toward price levels where real market participation occurred — not toward price levels where a clock happened to tick.
█ WHY KERNEL REGRESSION IS MACHINE LEARNING
The term machine learning describes algorithms that derive structure from data rather than from manually specified rules. Kernel regression satisfies this definition formally. The estimator computes:
ŷ = Σ [ w(i) × close ] / Σ
where each weight w(i) is determined by a kernel function — not by the programmer. The model decides, from the data, how much each historical bar should influence the current estimate. This is the same mathematical family as K-Nearest Neighbors, which weights neighbors by proximity. It is cited as a foundational non-parametric ML method in Bishop (2006) and Hastie et al. (2009), and is described as an attention mechanism in deep learning literature — the same concept behind transformer models. The claim is accurate, not cosmetic.
█ THE CORE INNOVATION — VOLUME WEIGHTING
Every existing Nadaraya-Watson implementation on PulseWire uses a pure time kernel:
• Standard NW: w(i) = K(i/h)
This means a bar with 10,000 shares traded and a bar with 10,000,000 shares traded receive identical weight if they are the same number of bars away. A thin overnight drift and a high-volume institutional session influence the regression equally. That is statistically incorrect — volume is a direct measure of how much informational content a price bar carries.
This script uses a volume-weighted kernel:
• This script: w(i) = vol_norm(i) × K(i/h)
where vol_norm(i) is the bar's volume normalized against the peak volume in the lookback window, raised to a configurable power exponent. The regression estimate is therefore:
ŷ = Σ [ vol_norm(i) × K(i/h) × close ] / Σ
High-volume bars anchor the curve. Low-volume bars — thin sessions, overnight drift, holiday trading — contribute minimally. The regression finds where the market actually agreed on price, not just where the clock recorded a tick.
█ THREE KERNEL FUNCTIONS
All three apply the same volume weighting. The choice controls how rapidly influence decays with time distance:
• Rational Quadratic (default) — heavier tail than Gaussian. Bars from 40–60 periods ago still contribute meaningfully if they had high volume. Best for daily and weekly charts where old high-volume levels remain structurally relevant.
• Gaussian — standard bell curve decay. Weight drops sharply with distance. Best for intraday charts where recency matters more than historical anchors.
• Epanechnikov — hard cutoff at the bandwidth boundary. Anything beyond h periods receives zero weight. Produces the most locally sensitive regression. Best for fast charts requiring tight responsiveness.
█ SIGNAL LOGIC
The envelope bands are placed at a configurable multiple of ATR, standard deviation, or a fixed percentage above and below the regression line. Three band width methods are available to match different volatility contexts.
Two signal modes are available:
• Reversion mode (default) — a signal fires when price crosses back through the band after an extension. The ▲ label appears on the bar where price returns inside the lower band. The ▼ label appears on the bar where price returns inside the upper band. This confirms reversion has begun rather than anticipating it.
• Extension mode — enable Signal on extension close to fire a signal the moment price closes outside a band. This is an early warning — useful for alerts before the reversion bar arrives.
Additional signal filters: minimum bars between signals to prevent repeat firing, optional slope direction gate so signals only fire when the regression slope agrees with the signal direction.
█ WHAT YOU SEE ON THE CHART
Regression line
The volume-weighted fair value curve. Cyan when slope is rising, magenta when falling. This is where the model estimates price should be given the recent history of high-participation price levels.
Envelope bands
Upper and lower boundaries built from ATR, standard deviation, or a fixed percentage. The upper band is tinted red — resistance zone. The lower band is tinted green — support zone.
Bar coloring — 4 states
• Bright red — price closed above the upper band. Extended, statistically stretched above fair value.
• Bright green — price closed below the lower band. Extended, statistically stretched below fair value.
• Dim silver — price inside bands, regression rising or falling, i.e normal bullish or bearish context.
The contrast between fully saturated outside-band bars and dimmed inside-band bars makes overextension immediately visible without reading the scale.
Signal labels
▲ REVERT or ▼ REVERT with VW=XX% showing the volume weight of the signal bar. A signal at VW=85% fired on a high-participation bar. A signal at VW=9% fired on a thin bar — lower confidence.
Signal bar highlighting
Two additional layers available: a background flash on the signal bar and a thick vertical line through the bar's full range. Both are independently toggleable. The vertical line uses width=4 — the maximum Pine Script allows — making the signal bar visually distinct even when zoomed out.
Dashboard
Displays: current regression value, slope direction, band width, Bar Vol Weight meter (▰▰▰▱▱▱) showing how much influence the current bar has on the regression, active kernel type, volume weighting status, percentage distance from the regression midline, and non-repainting mode status.
█ NON-REPAINTING
When Non-Repainting Mode is enabled (default), all calculations use a bar offset. The current bar's close does not enter its own regression estimate. Historical signals visible on closed bars will not change as new bars form. Disable this to see a predictive (repainting) version where the current bar participates in its own estimate — useful for visual exploration but not recommended for backtesting or alerts.
█ HOW TO USE
Core use case — mean reversion
This is a mean reversion tool. It works best when price is oscillating rather than trending directionally. The recommended workflow:
1 — Confirm a ranging regime with a separate regime classifier before acting on signals.
2 — Wait for price to reach or pierce the upper or lower band (bars turn bright red or green).
3 — Check the VW% in the signal label. Higher volume weight on the signal bar = higher confidence.
4 — Enter on the reversion signal (▲ or ▼ label). Stop beyond the wick of the signal bar.
5 — Target the regression midline as the primary exit. The % from mid dashboard row tracks progress in real time.
Timeframe guidance
The volume-weighting advantage increases with timeframe because higher timeframes produce more meaningful volume data per bar. H4 and Daily are the strongest timeframes for this tool. For intraday use, reduce the Volume Weight Power to 0.3–0.5 to soften the impact of individual volume spikes.
Quick-start settings by asset class
• Stocks daily: Window=100, Bandwidth=8, Vol Power=1.0, ATR×2.0
• Crypto daily: Window=80, Bandwidth=6, Vol Power=0.7, ATR×1.8
• Forex H4: Window=100, Bandwidth=10, Vol Power=1.0, ATR×1.5
• Indices H1: Window=120, Bandwidth=12, Vol Power=0.8, Stdev×2.0
█ SETTINGS REFERENCE
Kernel Settings
• Lookback Window — number of historical bars in the regression. Larger = smoother, more lag.
• Bandwidth (h) — controls how fast kernel weight decays with time. Higher = older bars still contribute.
• Kernel Type — Gaussian / Rational Quadratic / Epanechnikov. See kernel section above.
• RQ Alpha (α) — Rational Quadratic only. Lower = smoother mixture of length scales.
• Non-Repainting Mode — uses offset. Recommended ON for backtesting.
Volume Weighting
• Enable Volume Weighting — toggle the core innovation on or off. OFF = standard NW.
• Volume Normalization Window — peak volume reference window. Match or exceed the lookback window.
• Volume Weight Power — exponent on the volume weight. 1.0 = linear. 2.0 = quadratic. 0.5 = softer.
• Volume Weight Floor — minimum weight for any bar. Prevents zero-volume bars from being ignored entirely.
Envelope Bands
• Band Width Method — ATR (volatility-adaptive), Stdev (statistical), or Percent (fixed).
• ATR Length — period for ATR calculation.
• ATR / Stdev Mult — multiplier applied to ATR or standard deviation.
• Percent Offset % — used when Percent method is selected.
Signals
• Signal on band crossover — enable signals on band cross events.
• Signal on extension close — fire signal when price closes outside a band (early warning mode).
• Require slope change — only signal when regression slope direction agrees.
• Min bars between signals — gap guard to prevent repeat signals.
Visuals
• Dashboard — regression stats and live metrics table.
• Signal labels — ▲/▼ REVERT labels with volume weight percentage.
• Band fill — fill between upper and lower bands.
• Background flash — bright background color on signal bars.
• Vertical line on signal bar — thick line through full bar height at signal.
• Large dot marker — additional plotchar layer on signal bars.
• Dashboard position — Top Right / Top Left / Bottom Right / Bottom Left.
█ ALERTS
Seven alert conditions are available:
• Long signal — reversion through lower band
• Short signal — reversion through upper band
• Any signal — either direction
• Extended below lower band — early warning before reversion fires
• Extended above upper band — early warning before reversion fires
• Regression slope turned bullish
• Regression slope turned bearish
█ DISCLAIMER
This indicator is a decision-support tool. It does not constitute financial advice and does not guarantee future results. Past statistical patterns do not predict future price behavior. Always use proper risk management.
Method: Nadaraya-Watson Kernel Regression (Non-Parametric ML)
Innovation: Volume × Time Kernel Weighting
Kernels: Gaussian · Rational Quadratic · Epanechnikov
Signals: Mean Reversion (band crossover or extension)
Repainting: Configurable — non-repainting mode available Indicator
Indicator
Tectonic Regime Protocol [JOAT]Tectonic Regime Protocol
Introduction
Tectonic Regime Protocol is an open-source Pine Script v6 strategy that combines four analytical modules into a single rule-based trading system: a four-state regime classifier, a three-layer trend filter, a six-pillar confluence entry engine, and an adaptive exit module using ATR-based partial take-profit and a regime-adaptive trailing stop.
The strategy is designed for traders who want a fully automated systematic framework to study how regime-gating affects signal quality. Its primary hypothesis is that directional entries made when (1) the market is classified as a trending regime, (2) trend filters across multiple timeframes align, and (3) multiple structural, volume, and momentum inputs agree, produce statistically better outcomes than entries based on any single condition alone.
Strategy Default Properties
Initial capital: $100,000
Order size: 2% of equity per trade
Commission: 0.04% per side
Slippage: 2 ticks
Maximum open positions: 1
These settings represent realistic conditions for a funded discretionary trader using a liquid futures or equity instrument. The 2% equity sizing limits maximum theoretical drawdown from any single trade while providing meaningful position exposure. Commission and slippage values reflect typical institutional-grade execution costs for electronically traded instruments.
Core Concepts
1. Four-State Regime Classifier
The regime module classifies each bar into one of four states using ADX relative to a threshold and the ATR-to-SMA(ATR) ratio: Trend Bull, Trend Bear, Range High-Vol, Range Low-Vol. Only Trend states are eligible for entry. Range classifications suppress all entries regardless of how strong the confluence score is. This is the primary market context filter.
2. Three-Layer Trend Filter
Three independently computed trend conditions must all agree before a long or short entry is considered: close versus VWMA(200) determines whether price is above or below long-term value; the relationship between fast and slow HMA lines determines medium-term momentum direction; and the close versus a 50-period EMA on a higher timeframe provides multi-timeframe context.
3. Six-Pillar Confluence Score
The entry engine scores six market dimensions and requires the composite bull or bear score to exceed 50 of 100 (default, configurable) with a directional lead of at least 8 points above the opposing score. The six pillars are: market structure, OBV slope direction, KAMA position + RSI + WPR composite, swing-low liquidity sweep detection, ATR ratio in productive range, and Fractal Efficiency Ratio above 0.30.
bool longSetup = validRegime and regime == 1 and trendBull
and bull >= confThreshold and (bull - bear) >= confGap
and barstate.isconfirmed
4. Adaptive Exit Module
The exit logic uses partial exits at two take-profit levels. TP1 closes 50% of the position at 1.0× risk distance. TP2 closes the remaining position at 2.0× risk distance. After TP1 is reached, the stop is moved to the entry price (breakeven). The stop before TP1 uses a regime-adaptive ATR trail — the stop multiplier is lower in low-volatility regimes (tighter) and higher in high-volatility regimes (looser). A 30-bar time-based exit closes any remaining position if neither TP nor stop is reached.
5. Non-Repainting Architecture
All entry conditions are evaluated only when barstate.isconfirmed is true. The HTF EMA is requested with lookahead=barmerge.lookahead_off. Pivot-based conditions use confirmed pivot detection with symmetric lookback. No future bar references are used.
Default Settings and Performance Notes
The strategy is published with the default Properties values listed above. Results shown on the publication chart are generated using these exact settings. Commission of 0.04% per side is representative of typical electronic execution on liquid instruments.
Win rate alone does not characterize strategy performance. The strategy is designed around a two-tier partial exit structure targeting positive expectancy (wins × average win greater than losses × average loss) rather than high win rate. The profit factor and average R-multiple are the more relevant metrics for this type of system.
Input Parameters
Regime Module:
ADX Trend Threshold (default: 20)
ATR Ratio High-Vol Threshold (default: 1.2)
Trend Filter:
VWMA Length (default: 200)
Ribbon Fast HMA and Slow HMA lengths
HTF Timeframe for EMA(50) filter (default: 240)
Enable HTF Filter toggle
Confluence Engine:
Min Score (default: 50, range 50–95)
Min Direction Lead (default: 8)
Min FER (default: 0.30)
FER Lookback (default: 14)
Individual pillar weights (Structure, Volume, Momentum, Liquidity, Volatility, FER)
Exit Module:
TP1 RR Multiple (default: 1.0)
TP2 RR Multiple (default: 2.0)
Stop Multiplier for Low / Med / High Volatility Regimes
Max Bars Hold (default: 30)
How to Evaluate This Strategy
Apply it to a liquid instrument with sufficient historical data to generate more than 100 trades. Compare profit factor, Sharpe ratio, average R-multiple, and maximum drawdown — not win rate in isolation. Test it across at least two different instruments or timeframes to assess whether the results reflect genuine structural edge or data-fitting to one specific market.
The strategy is not optimized for any single market. Default parameters are deliberately conservative to avoid overfitting. Users who adjust parameters to improve backtested results should recognize that improvement on historical data does not guarantee improvement on future data.
Strategy Limitations
On lower-timeframe charts with short histories, fewer than 100 trades may result, reducing the statistical reliability of the backtest
The HTF filter uses request.security() with a higher timeframe EMA. In live trading, the HTF value updates when the higher timeframe bar closes, which may differ slightly from live server-side execution
ATR-based stops and targets mean position sizes and outcomes scale with volatility. In abnormally low-volatility environments, commission costs represent a larger proportion of expected gain
The time-based exit at 30 bars may close profitable positions before TP2 is reached in slow-moving markets
Backtested performance on any instrument does not predict future performance. Markets change, and parameters that produced edge historically may not do so in future regimes
Originality Statement
Combining a four-state regime classifier, a three-layer multi-timeframe trend filter, a six-pillar confluence score including Fractal Efficiency Ratio, and a partial-exit adaptive trailing stop system in a single non-repainting open-source strategy is an original integration of methods
The Fractal Efficiency Ratio as a pillar in a multi-factor entry score, and as a required gate condition for entry, is not present in existing open-source Pine Script v6 strategy publications as of this writing
The regime-adaptive stop multiplier — loosening in high-volatility regimes and tightening in low-volatility regimes — is an original stop calibration approach within this strategic framework
The dual entry mode (edge transition OR re-entry when flat with elevated score) increases signal frequency without compromising the fundamental regime and trend filter requirements
Disclaimer
This strategy is provided for educational and informational purposes only. It is not financial advice or a recommendation to buy or sell any financial instrument. Backtested results are simulated and do not represent real trading. Simulated results have inherent limitations and may not reflect actual trading outcomes due to market impact, execution differences, and changing market conditions. Past backtested performance does not guarantee future results. Trading involves substantial risk of loss. Always conduct independent due diligence and apply proper risk management before using any strategy with real capital. The author accepts no responsibility for trading losses resulting from use of this strategy.
Made with passion by jackofalltrades
Strategy
