Penunjuk
Pivot Premium Suite Nicolau EditionPivotPro Nicolau — Pivot Points + SuperTrend + EMA with the “Displacement” option
A professional all-in-one indicator combining three powerful technical
analysis tools into a single, clean, and highly configurable solution.
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📊 1. ADVANCED PIVOT POINTS
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Calculates and displays Pivot Points with full customization:
- Two calculation methods: Traditional and Fibonacci
- Configurable timeframe: Daily, Weekly, Monthly or Yearly
- Choose how many periods to display (current + previous)
- Labels positioned on Left or Right side of each line
- Individual color control for each level (P, R1, R2, R3, S1, S2, S3)
- Labels follow the line edge automatically — no overlap
- Alerts for price crossing any pivot level
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📈 2. PIVOT POINT SUPERTREND
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A unique SuperTrend implementation that uses Pivot Highs and Lows
as its center line instead of the traditional midpoint — making it
more reactive to actual market structure:
- ATR-based dynamic bands calculated from pivot-weighted center
- Buy/Sell signals rendered as plotshape (independent from labels)
- Optional Support/Resistance circles from pivot points
- Optional center line display
- Alerts for trend changes and Buy/Sell signals
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📉 3. EMA SUITE WITH SHIFT
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Three fully configurable Exponential Moving Averages with an
exclusive displacement feature:
- EMA 9, EMA 21, EMA 200 — all periods configurable
- Individual color for each EMA
- Each EMA has its own shift toggle and period input
- Positive shift = forward displacement (future projection)
- Negative shift = backward displacement (historical alignment)
- Visual crossover marker between EMA 9 and EMA 21
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⚙️ KEY FEATURES
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- Pivot numbers stay visible even when chart objects are hidden
- Buy/Sell labels are independent from Pivot labels
- All colors individually configurable
- Clean, non-overlapping label system
- Full alert support for all signals
Designed for traders who need precision, clarity and full control
over their chart without visual clutter.
Penunjuk
Smart SR Zones [JOAT]SMART SR ZONES
Support / resistance done properly. Most public SR scripts paint a horizontal line at every pivot, which produces wallpaper, not analysis. Smart SR Zones does the opposite — pivots are first detected with a volatility-aware engine, then clustered into zones, then scored by volume and touches, then filtered by spacing and distance. What ends up on the chart is the small handful of levels that actually matter for the current market state.
Pivot detection — preset-driven
A single Strength Preset selects the personality of the pivot engine:
Scalp — 4 left / 2 right, 0.4× ATR clustering tolerance, 4-bar minimum spacing. For 1–5m charts.
Local — 6 / 4, 0.5×, 8-bar. Tight zones from recent structure.
Swing — 15 / 8, 0.9×, 20-bar. The balanced default.
Major — 35 / 15, 1.4×, 50-bar. Wide macro zones.
Custom — every parameter is exposed for manual tuning.
The preset abstraction means you do not need to refit anything across timeframes — pick the read you want and the engine does the rest.
Clustering, not stacking
When two pivots fall within Cluster Tolerance × ATR of each other they are merged into a single zone, with the box span widened to cover both extremes. This is the difference between a "level" and a "zone": a level pretends price is precise, a zone respects the fact that liquidity sits in a band. The cluster tolerance is ATR-relative so the same setting works across symbols.
Touch counting, properly gated
A pivot must contribute to a cluster from a minimum bar spacing (preset-driven). Without this filter a chop within a zone gets counted as ten separate touches and inflates the strength score. With it, a zone earns its touch count from genuinely independent visits.
Volume-weighted strength + star rating
Each cluster accumulates the bar volume at every contributing pivot. The aggregate is converted to a 1–3 star rating relative to the strongest zone currently on the chart, and is shown in the zone label alongside the touch count. Zones can optionally be coloured by volume share so the visually loudest box is the one carrying the most demonstrated activity.
Zone of Interest (ZOI) — the headline filter
A zone earns the ZOI badge when all of these are true at the same time:
It has met the minimum-touches threshold (so it is real structure).
Its volume share is above the ZOI volume threshold (so it is meaningfully active).
It has not been touched recently — at least ZOI Quiet bars since the most-recent touch.
In other words, a ZOI is a high-quality level that the market is conspicuously not testing — and these are usually the next levels that matter. The ZOI gets a bright burlywood border with an optional animated pulse so it visually separates from the rest of the SR stack.
Distance hiding
A "Hide zones farther than %" input drops anything whose centre price is too far from current — so when you scroll into history the chart does not get cluttered with macro zones from another era. Set to 0 to keep everything visible.
Broken zones and dropped zones
Two optional historical layers:
Broken — zones that were physically closed through. Renders in a desaturated palette so you can see where structure failed without confusing it for active level.
Dropped — zones that were removed not by a break but by reorganisation, because newer / stronger pivots reshuffled the cluster set.
Both are off by default so a working chart stays clean.
Optional signal layer
Three small markers (all off by default) for traders who want execution hints rather than just structure:
Successful test — circle on bars that touched an active zone and rejected.
Retest — diamond when price returns to a broken zone from the opposite side, inside a configurable window.
Zone reaction — small diamond on a touch-with-hold, plus a text label on physical break events.
A configurable cooldown prevents back-to-back markers from the same zone.
Dashboard
A compact diagnostic table, positionable to any of nine corners, monospaced. Shows nearest support / resistance with distance, current ZOI status, active zone count per side, and the preset in use. A compact mode hides descriptions for narrow layouts.
Alerts
A single high-signal alert is exposed: Zone of Interest activation — fires on the first bar a zone qualifies as a ZOI. The other layers are visual diagnostics, not alert-grade; this is intentional, because the ZOI rule is the strongest filter in the script and is what you actually want to be notified about.
How to read it
Look at the chart and ignore everything except the ZOI-tagged zones and the stars. The stars tell you which historical levels have the most demonstrated activity; the ZOI badge tells you which of those have been deliberately avoided recently. The intersection — a star-rated ZOI close to price — is the cleanest level read this script can produce. Use the volume score and the touch count as a tiebreaker when multiple ZOIs are in play.
Suggested settings
Default Swing preset works well from 1H through 1D on liquid futures, FX, and crypto. Drop to Local for intraday execution and Scalp for tape-reading on minute charts. Major is for weekly / monthly macro reads. The ZOI volume threshold (70%) is intentionally strict — drop it to 50–60% if you want more frequent ZOI candidates.
Originality / what's reused
The vocabulary (pivot, cluster, touch count, broken zone, retest) is public-domain market-structure language. The implementation — the preset-driven engine, the ATR-clustering, the volume-weighted star rating, the ZOI rule (touches + volume share + quiet-period), the dropped-zone reorganisation logic, and the volume-share intensity colouring — is JOAT-original and tuned together as a single system. No third-party code reused.
Open source
Published open-source under the default Mozilla Public License 2.0. The source is fully documented inline — every helper is sectioned, every input has a tooltip, and the structural layers are separable so you can learn from any specific piece. Forks welcome with credit.
Limitations
SR is structural context, not a signal generator. Smart SR Zones does not print buy / sell labels — it prints zones, ratings, and a single high-quality ZOI alert. On extremely illiquid instruments the volume-share rankings will be noisy and the ZOI rule will fire less often; that is the right behaviour. Zones beyond the Pivot Memory horizon are dropped to stay under TradingView's 500-object cap.
—
-made with passion by jackofalltrades
Penunjuk
Delta Volume Profile ProDelta Volume Profile Pro is a volume profile indicator built upon the quadrant structure originally introduced by BigBeluga in the Quadro Volume Profile script. Full credit for the original concept and core logic goes to BigBeluga.
🔍 What it does
This indicator divides the visible price range into four quadrants relative to the current price and distributes volume across price bins, revealing where the most significant buying and selling activity has occurred above and below the market.
Each quadrant displays:
Upper Sell Quad — sell volume concentrated above the current price
Upper Buy Quad — buy volume concentrated above the current price
Lower Buy Quad — buy volume concentrated below the current price
Lower Sell Quad — sell volume concentrated below the current price
A Point of Control (PoC) dashed line marks the price bin with the highest volume in each quadrant.
Four percentage labels at the current price level show how total volume is distributed across all quadrants, allowing traders to quickly assess the balance between buying and selling pressure on both sides of the market.
⚙️ Original additions over BigBeluga's base
1. Proxy Volume Engine — works on any broker
Many brokers and CFD platforms do not provide usable native volume data. This indicator includes an internal map of 80+ symbols to their most liquid equivalents:
Forex pairs → (tick volume, CFD-compatible scale)
Metals (Gold, Silver, Platinum)
Crypto (BTC, ETH, etc.)
Oil, Gas →
Indices & Futures
The proxy is fetched automatically via request.security. You do not need to change any settings when switching between brokers — the indicator detects the symbol and loads the appropriate volume source.
2. Proxy-First Priority
Unlike a simple fallback system, this indicator uses the proxy as the primary volume source for all mapped symbols. This guarantees consistent, real volume data regardless of the broker you are charting on — whether EasyMarkets, FXCM, or any CFD provider. The native volume is only used if the proxy fails or if you explicitly enable "Force Native Volume" in settings.
3. Daily Session Mode
When enabled, the profile anchors to the start of the current daily session and resets automatically at each new day — useful for intraday traders who want to see only today's volume distribution.
4. Daily VWAP Anchor
An optional Volume Weighted Average Price line anchored to the daily session open, calculated using the same proxy volume logic as the profile for accuracy across all brokers.
📐 How to read the indicator
Profile bars (left and right of the vertical axis):
Left side bars = dominant directional volume per price bin
Right side bars = opposing volume per price bin
Deeper color = higher volume concentration at that price level
Longer bars = more activity at that price — key support/resistance zones
The four labels at current price:
SELL% | BUY%
SELL | BUY
──────────────────── ← current price
BUY% | BUY%
BUY | SELL
Upper left (SELL%) — percentage of total volume that was selling above current price
Upper right (BUY%) — percentage of total volume that was buying above current price
Lower left (BUY%) — percentage of total volume that was buying below current price
Lower right (SELL%) — percentage of total volume that was selling below current price
Point of Control (PoC) — dashed line:
Marks the single price level with the highest volume in each quadrant
Strong reference for support and resistance
📊 How to interpret the percentages
Example from chart — USDCAD 15M:
Upper: SELL 2.90% | BUY 3.75%
Lower: BUY 51.79% | SELL 41.57%
Reading:
51.79% of all volume below price was buying → strong buy accumulation below
41.57% of all volume below price was selling → significant sell pressure also present
Only 2.90% + 3.75% above price → very little activity above current price
Interpretation: price is near the top of the range with most activity below
General rules:
Large BUY% below + small SELL% above → bullish bias, buyers in control
Large SELL% above + small BUY% below → bearish bias, sellers in control
Balanced percentages on both sides → price in equilibrium, expect breakout
PoC line in lower quad with high BUY volume → strong support level
PoC line in upper quad with high SELL volume → strong resistance level
⚠️ Important notes
This indicator is a visual analysis tool. It does not generate buy or sell signals.
Past volume distribution does not guarantee future price behavior.
The proxy volume reflects tick volume from the mapped exchange, not actual traded notional value.
On weekends or when markets are closed, volume may be incomplete, affecting the profile.
⚙️ Settings reference
ParameterDefaultDescriptionUse Daily Session ModeOFFON: resets profile each day. OFF: fixed lookbackLookback Period200Bars used when Session Mode is OFFForce Native VolumeOFFON: uses chart's native volume instead of proxyPrice Bins60Number of horizontal price levelsProfile Offset60Distance from last bar (in bars)Upper/Lower QuadsONShow/hide each profile sectionPoCON/OFFShow/hide Point of Control per quadrantShow Daily VWAPONPlots the session VWAP lineBuy ColorGreenProfile buy side colorSell ColorRedProfile sell side colorVWAP ColorWhiteVWAP line color
🙏 Credits
Original quadrant volume profile concept and core structure:
BigBeluga — Quadro Volume Profile
www.tradingview.com
Released under Mozilla Public License 2.0
mozilla.org Penunjuk
Quantum Flux Bands [JOAT]Quantum Flux Bands
Quantum Flux Bands is an institutional-style regime detector. It stationarizes the price series via Fixed-Window Fractional Differentiation (FFD), runs a classical CUSUM change-point test on the stationarized stream, and draws a baseline that snaps to a new price level on every confirmed regime shift. Around the baseline, three percentile envelopes (50%, 68%, 90%) are drawn and modulated by a windowed Shannon entropy estimator so the bands narrow in low-noise regimes and widen in high-noise regimes.
What makes it different
Most regime filters hard-code a differentiation order (typically the first difference). FFD takes a real-valued differentiation order d between 0 and 1, retaining long-memory while making the series statistically stationary. This script chooses d adaptively from a rolling Hurst estimate so it responds to the market's persistence regime instead of being a fixed magic number.
The CUSUM trigger is fed by FFD-stationarized values, not raw returns. This reduces baseline whipsaws in trending markets that violate stationarity assumptions of classical CUSUM.
The bands are entropy-weighted. When the local windowed Shannon entropy is high (low signal-to-noise) the bands expand. When entropy is low (clean regime) they contract. The bands lock at the moment of a confirmed regime shift so they describe the regime under which the baseline was established.
How it works
A two-point Hurst estimator (rescaled-range over short and long windows) drives an adaptive differentiation order d in the range 0.30 to 0.90.
FFD weights are recomputed only when d drifts by more than 0.05 from its cached value. Caching keeps per-bar work near zero.
FFD weights are applied to a sliding window of close prices to produce a stationarized series.
Classical CUSUM tracks cumulative positive and negative deviations of the stationarized series from a running baseline reference, with user-configurable drift and threshold parameters.
When CUSUM exceeds the threshold, the baseline snaps to the current close and the trend state is set to bull or bear.
Inner, mid, and outer envelopes are drawn from percentile_linear_interpolation of the absolute distance between close and baseline, multiplied by an entropy modulator.
A bull probability is computed from the Abramowitz and Stegun standard-normal CDF on the signed band-distance and surfaced as a numeric label.
Reading the chart
Baseline line tinted purple in bull regimes, cyan in bear regimes, muted in neutral.
Six percentile band lines (upper and lower inner, mid, outer) with three pairs of atmospheric gradient fills calibrated so candles remain readable through every layer.
Optional iridescent candle recolor scales tint by signed regime score.
A probability label at the right edge of the chart shows the live bull probability.
Seven right-edge price labels, one per envelope level plus baseline, each sit at their own price.
Regime-shift timeline labels record every confirmed regime change with its baseline price and bull probability at the time of the shift.
A 21-segment vertical strength gauge at the right edge maps the continuous regime strength score onto a bull / bear / neutral scale, with a dashed sight-line drawing the gauge level back into the chart.
A short forward probability cone: two dashed segments at outer band levels with opacity scaled by class probability.
Signals
Bull / bear regime entry (CUSUM trigger with direction)
Outer band touch
Outer band rejection (wick pierces the outer band but the body closes back inside)
Baseline reclaim (close re-crosses the baseline)
All gated on barstate.isconfirmed or barstate.ishistory. No future references. No lookahead_on.
Inputs
Fractional Differentiation : FFD window length.
CUSUM : volatility period, drift parameter, threshold parameter.
Regime : Hurst short / long lookbacks, entropy window / bins / z-score length.
Bands : percentile lookback.
Visual : bullish, bearish, quantum purple, quantum cyan colors. Band visibility toggles. Iridescent candles. Regime pulse. Probability label.
Labels : right-edge level labels, regime timeline (offset off candle wicks by ATR), baseline reclaim markers (direction-sensitive Y offset, configurable minimum-bar spacing), band touch and rejection labels (configurable minimum-bar spacing per type), strength gauge, sight-line needle, probability cone, FFD memory label, entropy state strip.
Dashboard : position, size.
How traders use this
Mean-reversion fades from outer-band touches inside a stable regime (Hurst mean-reverting, low entropy z) are statistically supported setups.
Regime-shift entries : when the baseline snaps and the trend turns, the first inner-band retest is a higher-quality continuation entry than chasing the breakout bar.
Probability filter : use the bull probability label as a confidence multiplier for other systems. Below 30% or above 70% are the actionable zones.
Entropy context : high entropy z (band-multiplier expanded) is a low conviction, wider stops warning. Low entropy z (bands tight) is a high conviction, tighter stops green light.
Limitations
Fractional differentiation is a smoothing and filtering tool. It cannot create information that is not already in the price series.
CUSUM, like any change-point detector, lags real-time tops and bottoms. It is calibrated to balance whipsaw against responsiveness.
The two-point Hurst estimator is a fast approximation. For long-horizon classification it agrees with the full R/S statistic. For very short windows it is noisier.
Past regime persistence does not guarantee future regime persistence.
Compatibility
Pine Script v6 open-source indicator. Any symbol, any timeframe (longer timeframes give the FFD window more meaningful history). No external request.security calls. Non-repainting: regime shifts are committed on confirmed bars and baseline values are not retroactively rewritten.
Defaults
Mint and red bullish / bearish defaults. Purple and cyan quantum accents. Top-right medium dashboard. All on-chart visualizations on. Increase the FFD window for very high timeframes (daily and above) and decrease the percentile lookback for fast intraday charts.
Credits
Fractional differentiation methodology popularized by López de Prado, Advances in Financial Machine Learning (2018).
CUSUM change-point test as published by E. S. Page, Biometrika (1954).
Standard-normal CDF approximation per Abramowitz and Stegun (1964).
Penunjuk
Gatev Relative Value Arbiter [JOAT]Gatev Relative Value Arbiter
Introduction
Gatev Relative Value Arbiter studies relative value between the chart symbol and a selected peer using beta spread, z-score, stationarity, Kalman residuals, and OU speed.
This open-source indicator is designed as a context tool, not a standalone trading system. It focuses on explaining the current market state with restrained visuals and confirmed-bar logic where signals are used.
Core Concepts
1. Rolling Beta Spread
The chart log price is modeled against the peer log price with rolling beta and alpha.
2. Spread Z-Score
Residual spread is normalized to identify cheap and rich dislocations.
3. Kalman Residual
A recursive residual estimate adapts to changing pair behavior.
4. Stationarity and OU Speed
Correlation, beta drift, skew, kurtosis, and OU-style speed grade pair quality.
spread = logChart - (alpha + beta * logPeer)
Features
Peer relative-value model
Rolling beta and spread z-score
Kalman residual z-score
Stationarity and cointegration energy proxies
Cheap, rich, prime, broken, and fair-value states
Input Parameters
Peer symbol
Rolling beta and z-score lengths
Entry and exit z thresholds
Minimum correlation
Cooldown and display toggles
How to Use This Script
Choose a logically related peer. Cheap and rich states are most meaningful when pair validity and stationarity remain acceptable.
Limitations
The script uses historical OHLCV data and cannot know future prices.
Signals and states can be late during fast reversals because confirmed-bar logic is used to reduce repainting.
Model outputs should be interpreted with market context, risk controls, and independent analysis.
No visual state should be treated as a certain trade outcome.
Originality Statement
GRA is original in combining rolling beta arbitrage logic, Kalman residuals, OU speed, and stationarity grading.
Disclaimer
This indicator is provided for educational and informational purposes only. It is not financial advice, investment advice, or a recommendation to buy or sell any financial instrument. All calculations are derived from historical market data and may produce inaccurate readings in some market conditions. No indicator can predict future market behavior. Use proper risk management and independent judgment.
-Made with passion by jackofalltrades
Penunjuk
Live Footprint Center Frame📊 Live Footprint Center Frame
Live Footprint Center Frame is a footprint-style chart overlay designed to help traders study candle-by-candle volume behavior directly on the main chart. The script displays centered footprint frames around candles and breaks each candle into multiple price slots so volume structure can be viewed more clearly.
🔎 What It Does
The script visualizes estimated internal candle activity using lower-timeframe OHLCV data. It displays price-slot volume, delta behavior, POC, value area, imbalance markings, absorption-style highlights, delta bars, POC trail, and a compact HUD panel for quick market structure reading.
Key visual elements include:
• Footprint-style candle frames
• Price-slot volume ladder
• Estimated ask/bid style cell values
• Positive and negative delta coloring
• POC highlight
• Value Area highlight
• Imbalance arrows
• Absorption-style border highlights
• Small delta bar below candles
• POC trail between candles
• Compact HUD with ASK, BID, DEL, POC, VA, VOL, CVD, and bias information
🧠 General Logic
Live Footprint Center Frame uses lower-timeframe OHLCV data to approximate how volume is distributed inside each candle. The script divides the candle range into price slots, distributes lower-timeframe volume across those slots, and then calculates estimated delta, total volume, POC, value area, and balance information.
This is not true exchange-level bid/ask footprint data. It is an educational footprint-style approximation based on the data available through TradingView.
📌 Why It Is Useful
This tool can help traders study more than just candle open, high, low, and close. It gives a clearer visual view of where volume activity is concentrated inside the candle and how that activity changes from candle to candle.
It can be useful for observing:
• Where volume is concentrated
• How POC shifts between candles
• Whether delta supports or disagrees with price movement
• Where value area develops inside the candle
• Whether activity appears balanced or imbalanced
• Possible absorption-style areas
• Short-term volume structure around important price zones
🎨 Visual Reading Guide
Green-style cells show stronger positive delta behavior.
Red-style cells show stronger negative delta behavior.
Orange areas highlight the POC zone.
Blue-style areas highlight the value area.
Yellow borders can show absorption-style conditions.
Small delta bars below candles show candle delta direction and strength.
The HUD gives a quick summary of ASK, BID, DEL, POC, VA, VOL, CVD, and bias.
🧭 How To Use
1. Add the script to a clean chart.
2. Use intraday charts for clearer footprint-style reading.
3. Watch the POC area to see where the highest slot volume appears.
4. Compare candle delta with candle direction.
5. Use value area to understand where most candle activity is located.
6. Use imbalance and absorption highlights as context only.
7. Check the HUD for a quick summary of current candle conditions.
8. Combine this with market structure, support and resistance, liquidity zones, and proper risk management.
⚙️ Settings Overview
Lower timeframe precision controls the lower timeframe data used for the footprint approximation.
Closed bars to keep controls how many previous footprint candles remain visible.
Price slots per candle controls how many horizontal volume rows appear inside each candle.
Cell text controls whether cells show volume, delta, delta percentage, or estimated ask/bid style values.
Frame width adjusts the centered footprint frame width around each candle.
Live candle update allows the active candle footprint to update while the candle is forming.
POC trail connects POC movement between candles.
Value Area highlights the main volume zone.
Imbalance ratio controls imbalance sensitivity.
Absorption slot volume percentage controls absorption-style highlighting.
HUD settings control the compact panel position and visibility.
Color settings allow visual customization of bullish, bearish, neutral, POC, value area, frame, and delta elements.
⚠️ Limitations
This script uses TradingView-available OHLCV data and lower-timeframe calculations. It does not access true exchange order book data or true bid/ask footprint data on most symbols. Values can vary depending on symbol, timeframe, lower-timeframe availability, volume quality, and chart settings.
The live candle can update while it is still forming. Confirmed candles are more stable than the active candle.
✅ Educational Use Only
This script is provided for educational market analysis and visual order-flow style study. It does not provide financial advice, guaranteed results, or automatic trade decisions. Traders should use proper risk management and combine this information with their own analysis. Penunjuk
Veyra Delta Lens [JOAT]Veyra Delta Lens
Introduction
Veyra Delta Lens estimates delta pressure from OHLCV data and converts it into auction pressure, CVD z-score, participation entropy, absorption, and pressure-shift events.
This open-source indicator is designed as a context tool, not a standalone trading system. It focuses on explaining the current market state with restrained visuals and confirmed-bar logic where signals are used.
Core Concepts
1. Signed Volume Pressure
Candle close location and body impact estimate directional volume pressure.
2. CVD Normalization
Cumulative pressure is normalized so current pressure can be compared with recent history.
3. Participation Entropy
Volume concentration and close location distinguish balanced absorption from directional release.
4. Pressure Envelope
An auction mean and delta rails display pressure on the price chart.
delta = signedVolume * 0.65 + impactVolume * 0.35
Features
Estimated signed volume pressure
CVD z-score and impulse scoring
Absorption and divergence context
Auction mean and pressure rails
Sparse VX+ and VX- labels
Input Parameters
Delta smoothing and impulse memory
CVD normalization window
Participation entropy window
Event score and cooldown
Rails, trace, and candle toggles
How to Use This Script
Use VX+ and VX- labels as confirmed pressure shifts. Gold circles show absorption or divergence conditions aligned with the current regime.
Limitations
The script uses historical OHLCV data and cannot know future prices.
Signals and states can be late during fast reversals because confirmed-bar logic is used to reduce repainting.
Model outputs should be interpreted with market context, risk controls, and independent analysis.
No visual state should be treated as a certain trade outcome.
Originality Statement
Veyra is original in combining estimated delta, CVD normalization, entropy, auction rails, absorption, and divergence in one restrained overlay.
Disclaimer
This indicator is provided for educational and informational purposes only. It is not financial advice, investment advice, or a recommendation to buy or sell any financial instrument. All calculations are derived from historical market data and may produce inaccurate readings in some market conditions. No indicator can predict future market behavior. Use proper risk management and independent judgment.
-Made with passion by jackofalltrades
Penunjuk
Caelum Bias Ribbon [JOAT]Caelum Bias Ribbon
Introduction
Caelum Bias Ribbon is a multi-timeframe ALMA consensus ribbon. It evaluates whether 15m, 1H, 4H, 1D, and 1W horizons are aligned, mixed, or overheated.
This open-source indicator is designed as a context tool, not a standalone trading system. It focuses on explaining the current market state with restrained visuals and confirmed-bar logic where signals are used.
Core Concepts
1. ALMA Deviation States
Each timeframe creates an ALMA center and deviation threshold to classify bullish, bearish, or neutral state.
2. Consensus Voting
The script counts aligned timeframes to identify broad directional agreement.
3. Overheat Tracking
Directional runs are counted so stretched multi-timeframe conditions can be marked without predicting reversal.
4. Ribbon Visualization
Colored ALMA ribbons and fills show agreement without heavy labels.
consensus = bullCount >= gate ? 1 : bearCount >= gate ? -1 : 0
Features
Five-timeframe ALMA ribbon
Consensus and mixed-state detection
Overheat markers
Consensus candle coloring
Compact dashboard
Input Parameters
Deviation factor
ALMA length, offset, and sigma
Deviation length
Overheat run threshold
Display toggles
How to Use This Script
Use Caelum as a directional filter. Strong agreement supports trend-following context; mixed readings warn that timeframes are not aligned.
Limitations
The script uses historical OHLCV data and cannot know future prices.
Signals and states can be late during fast reversals because confirmed-bar logic is used to reduce repainting.
Model outputs should be interpreted with market context, risk controls, and independent analysis.
No visual state should be treated as a certain trade outcome.
Originality Statement
Caelum is original in combining ALMA deviation states, multi-horizon voting, run-length overheat logic, and a clean ribbon display.
Disclaimer
This indicator is provided for educational and informational purposes only. It is not financial advice, investment advice, or a recommendation to buy or sell any financial instrument. All calculations are derived from historical market data and may produce inaccurate readings in some market conditions. No indicator can predict future market behavior. Use proper risk management and independent judgment.
-Made with passion by jackofalltrades
Penunjuk
Penunjuk
Nyx Transition Corridor [JOAT]Nyx Transition Corridor
Introduction
Nyx Transition Corridor is an open-source probabilistic regime corridor. It estimates whether the current bullish, bearish, or neutral state has recently tended to persist, then draws adaptive volatility corridors around price. The indicator is built for context, probability, and controlled visualization rather than aggressive signal clutter.
Core Concepts
1. Regime State
The script classifies each bar as bullish, bearish, or neutral using EMA alignment, adaptive basis location, and return behavior.
2. Rolling Transition Model
Recent state transitions are counted to estimate continuation probability for the current state.
pBullBull = math.sum(fromBull * toBull, transitionLen) / math.sum(fromBull, transitionLen)
3. Adaptive Basis
The basis reacts faster when price movement is efficient and slower when the market is choppy.
4. Probability Corridor
ATR, volatility rank, and continuation probability determine the corridor width. Outer rails identify stretched conditions.
5. Compact Execution Rails
Optional small rails mark educational entry, stop, and targets when a probability reclaim or continuation event occurs.
Features
Three-state regime model: Bull, bear, and neutral states
Transition probability: Rolling persistence estimate for current state
Adaptive basis: Efficiency-weighted smoothing
Volatility-ranked corridor: Bands expand and contract with market stress
Confirmed HTF filter: Optional higher-timeframe EMA uses confirmed previous HTF data
Compact trade rails: Smaller educational rails to reduce chart obstruction
Dashboard: Shows probabilities, spread, efficiency, volatility rank, and HTF state
Input Parameters
Adaptive basis length controls centerline memory
Transition memory controls probability stability
Continuation threshold controls signal selectivity
Rail settings control optional educational projections
How to Use This Indicator
Step 1: Read the regime
The dashboard shows whether the model is bullish, bearish, or neutral.
Step 2: Compare probabilities
Large spreads between bull and bear odds indicate clearer directional context.
Step 3: Use the corridor
The corridor shows where price is trading relative to the adaptive probability field.
Indicator Limitations
Transition probabilities are historical estimates, not forecasts
Neutral markets can persist even when price briefly crosses the basis
The optional rails are visual projections and not trading advice
Originality Statement
Nyx Transition Corridor combines a state-transition model, efficiency-adjusted basis, volatility-ranked width, confirmed HTF filtering, and compact execution visuals. Its purpose is to map probabilistic state context, not to duplicate a standard moving-average band.
Disclaimer
This indicator is provided for educational and informational purposes only. It is not financial advice. Probability estimates are based on historical state transitions and do not predict future behavior.
-Made with passion by jackofalltrades
Penunjuk
Swing Volume Structure [JOAT] Swing Volume Structure
Introduction
Swing Volume Structure is an open-source market structure indicator focused on confirmed pivots, volume-backed breakouts, sweeps, retests, and compression. It is designed to keep structure analysis clean by confirming pivots with right-side bars and confirming actionable states on bar close.
The script helps traders distinguish ordinary swing movement from structure breaks that occur with volume expansion or sweep behavior.
Core Concepts
1. Confirmed Pivot Structure
Pivot highs and lows are confirmed using configurable left and right bars. Once confirmed, pivots are classified into structural context such as higher high, higher low, lower high, or lower low.
2. Volume Confirmation
Breakout states are scored using volume relative to a moving average. Expansion volume strengthens breakout quality, while quiet volume can mark compression.
3. Sweep and Reclaim Behavior
The script detects when price probes beyond a prior swing and then reclaims or rejects the level. This helps separate liquidity sweeps from clean breakouts.
4. Retest Logic
After a structural break, retest behavior can support continuation when price returns to the broken area and holds.
5. Entry and Exit Rails
Confirmed breakout or sweep states can draw entry, stop, TP1, and TP2 references using ATR and structure.
Features
Confirmed HH/HL/LH/LL structure: Pivots are classified after confirmation.
Volume-backed breakouts: Break quality is strengthened by relative volume expansion.
Sweep reclaim/reject states: Identifies failed breaks beyond prior swing levels.
Inside compression detection: Detects quiet, compressed conditions.
Supply/demand zones: Optional zones around important swing areas.
Entry/exit rails: Optional risk references for accepted states.
Candle tinting: Bars can reflect current structure state.
HUD: Shows state, bias, pivot class, volume, nearest support/resistance, score, and bar counts.
Alerts: Long breakout, short breakout, bullish sweep, bearish sweep, inside compression, and volume expansion.
Input Parameters
Structure: Pivot Left, Pivot Right, ATR Length, Zone ATR Thickness, Zone Extension Bars.
Volume and Signals: Volume Average Length, Expansion Multiplier, Quiet Compression Threshold, Minimum Breakout Score, State Cooldown Bars.
Risk and Visuals: Stop ATR Buffer, TP1 R, TP2 R, Rail Projection Bars, Tint Candles by State, Connect Confirmed Swings, Show Supply/Demand Zones, Pivot Labels, Active Support/Resistance, Structure HUD.
How to Use This Indicator
Step 1: Read structure bias
Use the HUD and swing context to identify whether structure is improving, deteriorating, or balanced.
Step 2: Separate breakouts from sweeps
A breakout shows acceptance beyond structure. A sweep shows a probe and rejection or reclaim. These are different conditions.
Step 3: Check volume
Volume expansion can increase the importance of a break. Quiet volume can identify compression or lower-conviction movement.
Indicator Limitations
Pivots confirm only after the configured right bars complete.
Volume confirmation depends on the quality of the symbol's volume feed.
Supply/demand zones are approximations around swing areas, not exact order book data.
Breakout and sweep states can fail during high-volatility reversals.
Originality Statement
Swing Volume Structure is original in how it combines confirmed pivot classification, volume expansion scoring, sweep/reclaim logic, retests, compression states, optional zones, candle states, and ATR risk rails into a single structure tool.
Disclaimer
This script is provided for educational and informational purposes only. It is not financial advice or a trade recommendation. Structure signals are based on historical candles and can fail. Use proper risk management.
Made with passion by jackofalltrades
Penunjuk
VWAP Daily Bands StandardVWAP Daily Bands is a volume-weighted average price indicator anchored to the daily session, enhanced with adaptive standard deviation bands designed to work accurately across all asset classes — including Forex, Crypto, Commodities, Indices, and Stocks.
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THE PROBLEM THIS INDICATOR SOLVES
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Most VWAP band implementations calculate standard deviation using only intraday price variance. This creates a well-known flaw: at the start of each session, when very few bars have been processed, the bands collapse to near zero and are practically useless. As the session progresses, the bands gradually widen — but asymmetrically, because early price swings distort the variance calculation.
This indicator solves that with a fixed daily ATR seed.
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HOW THE ATR SEED WORKS
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Before the session opens, the indicator fetches the previous day's closing price and ATR from the daily timeframe. These two fixed values are used to calculate a minimum band width that holds constant throughout the entire trading day — it does not fluctuate with intraday price movement.
The standard deviation used for the bands is then taken as the larger of two values: the real-time intraday price variance, or the fixed ATR-based seed variance. This means the bands are always at least as wide as the prior day's volatility warrants, while still expanding naturally when intraday price action is more volatile than usual.
The result is symmetric, stable bands from the very first bar of the session.
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PROXY VOLUME ENGINE
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Many brokers and CFD platforms do not provide real volume data. Without volume, a VWAP calculation loses its core meaning.
This indicator includes a built-in Proxy Volume Engine that automatically detects the current symbol and maps it to a liquid equivalent source with real volume data. For example, XAUUSD is mapped to COMEX:GC1!, EURUSD to FX:EURUSD, BTCUSD to BINANCE:BTCUSDT, and so on — covering over 80 symbols across all major asset classes. If the platform provides native volume, it is used directly. If not, the proxy volume is applied transparently with no action required from the user.
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WHAT IS PLOTTED
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• VWAP (white) — daily anchor VWAP calculated from HLC3, reset at the start of each session, weighted by effective volume.
• Upper bands (cyan) — 1σ, 2σ, and 3σ above the VWAP, indicating potential resistance or overbought zones.
• Lower bands (red) — 1σ, 2σ, and 3σ below the VWAP, indicating potential support or oversold zones.
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SETTINGS
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• Show Daily VWAP — toggle the VWAP line on or off.
• Show Band 1σ / 2σ / 3σ — toggle each band pair individually.
• Band Width Multiplier — scales all bands up or down proportionally (default 1.0).
• Daily ATR Period — controls how many days are used to calculate the ATR seed (default 5).
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COMPATIBLE WITH
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Forex majors, minors and exotics · Crypto (via Binance) · Gold, Silver, Platinum, Palladium · Oil and Natural Gas · Agricultural commodities · US Dollar Index · Major global indices: DOW, NASDAQ, S&P 500, Nikkei, DAX, FTSE, CAC, MIB, ASX, Hang Seng · Top US and European stocks.
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NOTES
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The VWAP calculation uses Pine Script's native HLC3-based volume-weighted average price as its mathematical foundation. The ATR seed mechanism, Proxy Volume Engine, and adaptive band logic are original contributions developed specifically for this indicator to address real limitations found in standard VWAP band implementations. Penunjuk
Regime Execution Strategy [JOAT]Regime Execution Strategy
Introduction
Regime Execution Strategy is an open-source TradingView strategy that integrates adaptive forecast context, extreme-channel state, trend pressure, relative volume, and EMA structure into a single rule-based execution model. The strategy is designed to be realistic, non-repainting, and readable rather than curve-fit to one symbol.
The problem it solves is trade filtering. A single signal source can trigger too often in poor conditions. Regime Execution Strategy requires multiple independent votes before entries are allowed, then uses ATR-based stop and target logic for consistent risk framing.
Core Concepts
1. Adaptive Forecast Bias
The strategy estimates a dynamic mean and band structure. Price above or below the adaptive mean contributes to directional bias.
2. Extreme Channel Bias
Persistent upper and lower channel levels define a midpoint and directional state. The channel contributes a second independent vote.
3. Pressure and Structure Gate
Momentum, pullback location, and fast/slow EMA structure contribute to the regime score. A minimum vote count and relative-volume filter are required before entry.
longSignal = barstate.isconfirmed and bullVotes >= voteThreshold and bullRegime and (longBreakout or longReclaim)
4. ATR-Based Risk Management
Stops and targets are derived from ATR and position average price. The strategy also includes max drawdown and max intraday filled order risk controls.
Features
Integrated regime detection: Forecast, channel, pressure, and EMA structure combine into a regime score
Multi-vote entry logic: Entries require several independent components to align
More active defaults: Default RVOL and regime thresholds are permissive enough to participate across many timeframes
ATR stop and target: Risk is framed with volatility-adjusted exits
Bias-flip exits: Positions can close when the opposing regime gains enough votes
Risk controls: Max drawdown and max intraday filled orders are included
Overlay visuals: Forecast bands and adaptive channel context can be displayed on chart
Top-right dashboard: Regime, score, pressure, RVOL, votes, position, band width, and setup
Alerts: Long and short setup events
Input Parameters
Forecast:
Source, Forgetting Factor, Regression Horizon, Band Multiplier, ATR Blend, and Rebase Interval
Regime:
Fast EMA and Slow EMA: Trend structure references
Pressure Length: Momentum and pullback window
Pressure Threshold: Minimum pressure vote threshold
Min RVOL: Participation filter
Min Votes: Minimum number of aligned components for entries
Risk:
Stop ATR: Stop distance multiplier
Target ATR: Target distance multiplier
Max Drawdown %: Strategy risk halt setting
Max Intraday Filled Orders: Limits daily trade frequency
How to Use This Strategy
Step 1: Read the dashboard regime before judging entries.
Step 2: Use votes and pressure to understand why a setup qualified.
Step 3: Review stop and target settings for the symbol and timeframe being tested.
Step 4: Evaluate results across multiple markets and date ranges, not one optimized window.
Strategy Limitations
This strategy is not optimized for a specific symbol or timeframe
More active defaults can increase trade count and also increase exposure to choppy periods
Backtest fills are simulated by TradingView and may not match live execution
All entry signals use confirmed-bar logic, so entries can occur after the intrabar move has begun
Strategy performance should be evaluated with realistic commission, slippage, and position sizing
Originality Statement
Regime Execution Strategy is original in its integration of adaptive forecast bias, extreme-channel state, pressure voting, relative volume gating, EMA structure, ATR exits, and dashboard reporting into one open-source strategy. It does not copy third-party source code.
Disclaimer
This open-source strategy is for educational and informational purposes only. It is not financial advice or a recommendation to buy or sell any instrument. Backtested results do not predict future performance. Trading involves substantial risk, and users are responsible for their own risk management.
-Made with passion by jackofalltrades
Strategi
Aureon Pressure Lens [JOAT]Aureon Pressure Lens
Introduction
Aureon Pressure Lens is an open-source pressure oscillator designed to classify directional participation, conviction, and transition states in a separate pane. It blends price impulse, EMA structure, momentum, range location, candle body pressure, and relative volume into one bounded score.
The problem it solves is signal quality. A single oscillator can fire during weak, low-participation moves. Aureon Pressure Lens requires pressure, signal-line behavior, relative volume, and component consensus to align before confirmed buy or sell labels appear.
Core Concepts
1. Multi-Component Pressure Blend
The oscillator uses several independent inputs: impulse from prior price, fast/slow structural slope, normalized momentum, range position, and candle body direction.
2. Tanh Normalization
Each component is normalized into a stable bounded range so one volatile input does not dominate the entire reading.
pressureScore = f_tanh(pressureBlend * 1.60) * 100.0
signalLine = ta.ema(pressureScore, signalLength)
3. Consensus Filter
The confidence reading measures how closely the components agree. A signal must satisfy the minimum conviction threshold before it can print.
4. Relative Volume Participation
The script measures current volume against a moving average and uses that reading as a participation gate. The default is permissive enough for broad use while still filtering extremely quiet conditions.
Features
Separate-pane pressure score: Bounded -100 to +100 directional pressure reading
Signal line: Smoothed reference for pressure resets and crossovers
Gradient pressure color: Score color transitions between bearish, neutral, and bullish states
Pressure cloud: Optional fill between pressure and signal line
Confirmed BUY/SELL labels: Closed-bar events filtered by consensus and RVOL
Top-right dashboard: State, bias, pressure, signal, RVOL/conviction, and action
Alerts: Bullish and bearish confirmed pressure resets
Input Parameters
Calculation:
Core Lookback: Main analysis window for impulse and range context
Fast Lens / Slow Lens: EMA structure lengths
Signal Lens: Smoothing length for the signal line
Pressure Sensitivity: Normalization intensity
Min Relative Volume: Participation gate for labels
Min Conviction: Minimum component agreement required for labels
How to Use This Indicator
Step 1: Read the pressure score relative to zero.
Step 2: Use the cloud and signal line to identify pressure resets.
Step 3: Check dashboard conviction and RVOL before acting on labels.
Step 4: Combine with an overlay structure or regime tool for full chart context.
Indicator Limitations
The oscillator measures current pressure, not future price direction
Relative volume can behave differently on symbols with limited volume data
Choppy markets can create repeated signal-line crosses
Confirmed labels appear only after the bar closes
Originality Statement
Aureon Pressure Lens is original because it combines impulse, structure, momentum, range position, candle body pressure, relative volume, and component consensus into a single closed-bar pressure engine with a dedicated dashboard. It does not copy third-party source code.
Disclaimer
This open-source indicator is for educational and informational purposes only. It is not financial advice. Markets can change quickly, and no pressure reading guarantees a future move. Use risk controls and independent analysis.
-Made with passion by jackofalltrades
Penunjuk
Concord Execution Mandate [JOAT]Concord Execution Mandate
Introduction
Concord Execution Mandate is an open-source strategy that combines regime classification, higher-timeframe bias, structure breaks, daily pivot context, reversion-basis reclaim logic, and divergence safety into one execution framework. It is designed to test whether directional entries improve when multiple context layers are aligned rather than relying on a single trigger.
The problem this strategy solves is unstructured execution. Many strategies either enter too often without context or wait for perfect alignment so long that they never engage. Concord Execution Mandate uses a softer confluence model that can still trade frequently while preserving directional context, confirmed-bar logic, realistic costs, and explicit risk controls.
Core Concepts
1. Regime And Context Layer
The strategy starts with an adaptive range-state engine supported by ADX, choppiness, and higher-timeframe EMA bias. These inputs do not all act as hard blockers; instead, they contribute to whether the environment is favorable enough for execution.
2. Structural And Rotation Triggers
Entries can come from confirmed bullish or bearish BOS behavior, continuation crosses back through the regime filter, or more aggressive rotation entries through the daily pivot, reversion basis, or short EMA.
3. Soft Alignment Model
Daily pivot bias, EMA weave bias, geometry bias, and regime location are combined into a directional alignment score. The strategy requires enough agreement to avoid fully random entries, but it does not require every filter to align perfectly before acting.
4. Risk Management
Stops are based on the closer of pivot structure or ATR distance. Targets are expressed as a reward multiple of live risk, and a trailing stop can activate only after price reaches a configurable multiple of initial risk. Context-flip exits can close trades early when directional state changes materially.
Features
Adaptive regime filter: Core state engine for directional context
Higher-timeframe bias: Optional EMA-based external direction filter
Structure triggers: Confirmed BOS logic using stored pivots
Continuation and rotation entries: Additional execution paths beyond BOS
Daily pivot and EMA weave context: Location-versus-bias inputs for alignment scoring
Reversion reclaim logic: Optional re-entry through a mean basis before entry
Divergence safety filter: Optional block on fresh opposing divergence
ATR and structure-based stops: Dynamic risk anchoring
Reward targets and ATR trailing: Structured exit management
Context-flip exits: Early closure when regime or bias reverses
Realistic defaults: Percent-of-equity sizing, commission, and slippage are defined in the strategy properties
Default Strategy Properties
Initial capital: 100000
Default order size: 5 percent of equity
Commission: 0.02 percent
Slippage: 2 ticks
Order processing: on bar close
Pyramiding: 0
How to Use This Strategy
Step 1: Read the dashboard to confirm the current regime, structural state, and whether the entry stack is armed.
Step 2: Use the strategy on instruments and timeframes where directional movement and retracement behavior are both visible enough to generate a meaningful sample.
Step 3: Review whether aggressive rotation entries or stricter reclaim filters better match the market being tested.
Step 4: Keep the published chart clean and use the same Properties values shown in the strategy description when presenting results.
Step 5: Evaluate the strategy using a broad sample of trades rather than isolated trades or one short backtest segment.
Strategy Limitations
This strategy still relies on lagging structure confirmation and can miss the first portion of fast reversals
More aggressive settings can increase trade count at the cost of lower selectivity
Higher-timeframe bias can conflict with local execution context during turning points
Backtest results depend on symbol, timeframe, session behavior, and execution assumptions
This strategy is designed to be realistic, not optimized for one narrow market condition
Originality Statement
Concord Execution Mandate is original in how it integrates adaptive regime logic, structural breaks, rotation entries, soft alignment scoring, reclaim filtering, divergence safety, and layered exit management into one execution framework. The combination is intentional because the strategy is designed to test whether context-aware execution can remain active without devolving into random signal generation.
Disclaimer
This strategy is provided for educational and informational purposes only. It is not financial advice and does not guarantee future performance. Backtests are based on historical data, configured assumptions, and simulated order handling. Always validate behavior independently and use appropriate risk management.
-Made with passion by jackofalltrades
Strategi
Mercator Pressure [JOAT]Mercator Pressure
Introduction
Mercator Pressure is an open-source institutional-style pressure oscillator built to measure directional force using a blended model of candle pressure, close-location behavior, range expansion, optional volume impulse, and volatility-channel context. The goal is to capture not just whether momentum is positive or negative, but how forceful and structurally aligned that movement is.
The problem Mercator Pressure solves is shallow momentum interpretation. Many oscillators react to price movement but fail to distinguish between weak drift, strong displacement, location inside a volatility envelope, and divergence between price and internal force. Mercator Pressure combines those dimensions in one panel and adds confirmed divergence logic, threshold regimes, layered gradients, and a live dashboard.
Core Concepts
1. Weighted Candle Pressure Engine
The core model scores each bar using a weighted blend of body impulse, close location, range expansion, and optional relative volume impulse. This helps the oscillator react differently to high-conviction bars than to passive movement.
2. Volatility-Channel Context Engine
Pressure is not evaluated in isolation. The script also measures where price sits inside an adaptive volatility envelope and uses that context as part of the composite regime model.
3. Composite Regime and Signal Layer
The pressure and context models are blended into a smoothed composite oscillator and signal line. Regime state is then derived from threshold behavior and internal persistence.
4. Confirmed Divergence Detection
Both regular and hidden divergence are supported using pivot-confirmed logic, which keeps the divergence framework more stable than naive visual divergence methods.
5. Institutional Panel Styling
Mercator Pressure uses layered fills, gradient regime cues, restrained optional divergence markers, and a top-right dashboard rather than retail-style arrow spam.
Features
Multi-factor pressure engine: Body, close location, range expansion, and optional relative volume
Volatility envelope context: Internal force is blended with channel position
Composite oscillator and signal line: Regime interpretation is smoother and more stable
Regular and hidden divergence: Pivot-confirmed divergence conditions
Confirmed-bar event gating: Alerts and key events can be evaluated on closed bars
Layered gradient fills: Smooth panel depth instead of harsh histogram clutter
Regime background tint: Visual context in the panel
Top-right dashboard: Live state readout for regime, slope, context, and divergence
Optional divergence markers: Uses professional square and diamond markers, not arrows
Alertconditions: Regime flips, signal crosses, expansions, and divergences
How to Use This Indicator
Step 1: Read the Composite Line Versus Signal
When the composite line is above the signal and above key thresholds, internal pressure is supportive. The opposite applies during bearish pressure.
Step 2: Check Regime State
Use the dashboard and panel tint to determine whether the script sees a bullish, bearish, or neutral pressure regime.
Step 3: Watch Expansion Conditions
Expansion events are stronger than ordinary threshold crosses because they imply pressure is extending into a more forceful state.
Step 4: Use Divergence as Context
Divergence is best used as a warning or contextual signal, not as a blind reversal trigger.
Indicator Limitations
Divergence only confirms after pivots confirm, which introduces natural delay by design
Pressure is a proxy model derived from chart data, not exchange-level order flow
The composite engine is adaptive and may behave differently across very low-volatility versus very high-volatility symbols
This script is best used as a directional-quality filter or context tool, not a standalone trading system
Originality Statement
Mercator Pressure is original in the way it combines weighted candle pressure, volatility-envelope context, regime hysteresis, and pivot-confirmed divergence inside one coordinated panel. Its value comes from force measurement, contextualization, and divergence structure rather than from any one common oscillator formula.
Disclaimer
This indicator is provided for educational and informational purposes only. It is not financial advice. Pressure and divergence readings are derived from historical price and volume behavior and do not guarantee future results.
- Made with passion by jackofalltrades
Penunjuk
Concordance Strategy [JOAT]JOAT Concordance Strategy
Introduction
JOAT Concordance Strategy is an open-source multi-factor TradingView strategy designed to integrate the JOAT indicator stack into one execution framework.
It combines regime context, liquidity interaction, retracement logic, pressure confirmation, channel behavior, and participation filters to decide when enough independent evidence exists to justify a trade.
The problem it solves is single-factor dependency.
Trend-only systems often chase poor location.
Liquidity-only systems can trigger too early.
Oscillator-only systems can fade strong directional auctions.
Retracement-only systems can buy weak pullbacks without sponsorship.
This strategy attempts to solve that by requiring overlap.
It does not assume one tool family is sufficient on its own.
Instead, it asks whether multiple analytical dimensions agree.
That agreement is what the strategy calls concordance.
Core Concepts
1. Regime Gate
The strategy first evaluates local and higher-timeframe baseline structure, slope, volatility state, and directional control.
2. Hard and Soft Directional States
The system uses stronger and softer directional states instead of an all-or-nothing gate.
3. Liquidity and Structure Stack
Entries consider sweep behavior, break state, and displacement.
4. Retracement and Confluence Layer
Local and HTF retracement context help determine whether price is pulling back into a structurally meaningful area.
5. Pressure Confirmation
Pressure logic attempts to confirm that price action has sponsorship behind it rather than only visual momentum.
6. Sigma Channel State
Channel logic helps determine whether price is re-entering a directional path or fading from extension.
7. Participation Filter
Relative volume and delta-style participation help avoid weak sponsorship environments.
8. Risk and Exit Model
The strategy uses structure-aware ATR stops, partial exits, break-even logic, trailing behavior, and optional time exits.
Features
Integrated multi-factor entry model: regime, liquidity, retracement, pressure, channel, and participation
More active soft-entry path: allows more trades while keeping directional structure
Confirmed-bar logic: entries use confirmed state conditions
Equity-risk sizing: position size is derived from risk per trade
ATR and structure-aware stops: volatility and market structure both matter
Two-stage profit taking: TP1 and TP2 split the exit logic
Break-even and trailing logic: protects trades after expansion
Time-based exit: removes stale positions when needed
Dashboard: regime, confluence, pressure, ledger, and position state are displayed
Strategy Properties Used by Default
Initial capital: 100000
Commission type: percent
Commission value: 0.02
Pyramiding: 0
Position sizing: equity-risk based
Trade management: partial exits, break-even logic, ATR trail, optional time exit
How to Use This Strategy
Step 1: Treat it as a research framework rather than a promise of future performance.
Step 2: Evaluate it across multiple markets and timeframes because the more permissive logic should produce broader participation than the earlier strict version.
Step 3: Judge the quality of the trade distribution rather than focusing on one isolated metric.
Step 4: Respect the compromises between selectivity and trade frequency.
Step 5: Use realistic expectations and avoid reading a single backtest as proof of repeatable future outcomes.
Strategy Limitations
The strategy still depends on confirmed conditions and can therefore enter later than a discretionary trader
Trade frequency and quality vary significantly by symbol and timeframe
Default settings are general-purpose and may not be ideal for every market
Optimizing too aggressively can become curve fitting
Backtest results are hypothetical and do not guarantee future performance
Originality Statement
This strategy is original in how it requires agreement across regime, liquidity, retracement, pressure, channel, and participation modules before or during entry qualification.
The components are not merged simply to produce a busier system.
Each one addresses a different failure mode in execution.
Their overlap is the basis for participation.
Disclaimer
This strategy is provided for educational and informational purposes only.
It is not financial advice.
Backtest results are hypothetical and depend on assumptions, settings, and market selection.
They do not guarantee future returns.
Trading involves substantial risk of loss.
Always validate assumptions independently and use responsible risk management.
Best Use Cases
Researching whether cross-confirmation improves selectivity over single-factor systems
Studying how regime, liquidity, retracement, and participation interact inside one strategy
Comparing trade frequency across markets and timeframes after the softer entry expansion
Testing realistic risk-management assumptions inside a multi-layer strategy
Interpretation Notes
This strategy should be evaluated as a process, not as a single summary metric.
Trade count matters.
Distribution of trades matters.
How the system behaves across different instruments matters.
The softer entry path was added to prevent the strategy from becoming too inactive, especially on higher timeframes.
That makes the strategy more usable for broad testing while still preserving directional structure.
Publication Notes
This strategy should be published with a clean chart and realistic default Properties.
If showing results, the description should stay grounded and avoid implying that one test run guarantees future outcomes.
The chart image should make the strategy entries and exits easy to understand.
-Made with passion by jackofalltrades
Evaluation Framework
1. Start by checking whether the strategy is active on the instrument and timeframe you care about.
2. Compare trade count before and after threshold changes.
3. Review whether trade quality remains acceptable as activity increases.
4. Study the interaction between regime, liquidity, pressure, and participation at entry.
5. Judge the strategy by distribution and robustness rather than one isolated metric.
Why This Matters
The strategy exists to test whether agreement across multiple independent analytical layers can improve execution quality.
That research question is more important than any one headline metric.
Open-Source Notes
This strategy is published open source so users can inspect how the modules overlap and how the risk model is applied.
Who This Is For
This strategy is for users who want to study how multiple context layers can be combined inside one execution model.
It is not intended for anyone looking for a one-click guarantee.
Summary
JOAT Concordance Strategy is best understood as a structured research tool.
It exists to test whether regime, liquidity, retracement, pressure, channel, and participation agreement can improve decision quality.
Additional Notes
This strategy should be judged with realistic commission and execution assumptions.
It should also be evaluated on enough trades to produce a meaningful sample.
The defaults are intended to stay grounded rather than theatrical.
Strategi
Aperture Imbalance Register [JOAT]Aperture Imbalance Register
Introduction
Aperture Imbalance Register is an open-source Pine Script v6 indicator built to detect, rank, and manage directional imbalance zones in a more structured way than a basic fair value gap overlay. Instead of marking every raw three-candle gap and leaving the trader to judge which ones matter, the script builds a register of active bullish and bearish imbalance zones, measures their internal lower-timeframe participation, assigns a quality score, tracks mitigation progress, and keeps the resulting stack visible with a compact institutional-style dashboard.
The problem this indicator solves is selectivity. Many imbalance tools show too many zones, retire them too slowly, or provide no context for which inefficiencies are likely to matter. Aperture Imbalance Register focuses on the active imbalance stack and grades each register by combining gap displacement with lower-timeframe volume participation. That lets the trader see not only where imbalance exists, but how concentrated the internal participation was when the zone formed.
The script is designed for traders who use imbalance as part of a broader market-structure process. It is not trying to predict every reversal. It is designed to answer practical chart questions: where are the open directional inefficiencies, how strong are they, how much of each zone has been mitigated, and whether the current stack favors bullish or bearish continuation pressure.
Because the script uses Pine Script v6 lower-timeframe arrays, the register is not just a visual box painter. It uses lower-timeframe intrabar data to build participation histograms inside each zone, identify the local point of control of the imbalance, and display whether a register still has open space or has already been substantially repaired by later price action.
Core Concepts
1. Confirmed Bullish and Bearish Gap Detection
The script detects a bullish register when the current low is above the high from two bars ago and the middle bar confirms continuation. It detects a bearish register with the inverse condition. A sigma-style filter based on the statistical size of the gap helps reject weaker dislocations:
bool confirmedBullGap = enoughGapHistory and barstate.isconfirmed and low > high and high > high and bullGapSigma > gapSigma
bool confirmedBearGap = enoughGapHistory and barstate.isconfirmed and high < low and low < low and bearGapSigma > gapSigma
This means the indicator is not plotting every minor price skip. It requires both structural displacement and a size filter before a new register is added to the active stack.
2. Lower-Timeframe Participation Ranking
Once a gap is confirmed, the script requests lower-timeframe `close` and `volume` data using `request.security_lower_tf()` and maps intrabar participation into configurable bins across the zone. That participation profile is then used to score the register.
This matters because not all imbalances are equal. Some form with broad participation spread across the full zone. Others form with concentrated acceptance in one portion of the gap. The participation histogram helps identify where the market transacted most heavily inside the register and where the imbalance may be most meaningful on a retest.
3. Quality Scoring and Register Prioritization
Each register receives a quality score derived from the concentration of lower-timeframe participation plus the size of the gap sigma event. Higher-quality zones get more visual emphasis, stronger edges, and greater dashboard influence.
In practice, this creates a hierarchy. The trader does not need to treat every imbalance equally. The register list naturally emphasizes the zones with stronger displacement and denser participation.
4. Mitigation Tracking and Lifecycle Management
Open imbalance is not enough. What matters is whether the zone remains unfilled. The script measures mitigation depth as price trades back into the register and updates the display from open to partial mitigation to fully filled. When the `Retire Fully Mitigated Zones` option is enabled, fully repaired or invalidated zones are removed from the active stack.
This keeps the chart cleaner and prevents stale boxes from dominating the view after the market has already rebalanced the inefficiency.
5. Participation Histogram and Local POC
Each register can display a small internal histogram showing participation intensity by price segment. The maximum participation bin defines the register’s local point of control, and that level is drawn as a line through the zone.
This gives the register more structure than a plain box. Instead of just seeing the outer bounds, the trader can see where activity concentrated inside the imbalance.
Features
Bullish and bearish imbalance registers: Detects confirmed gap-style inefficiencies in both directions using confirmed-bar logic
Lower-timeframe participation model: Uses lower-timeframe arrays to rank each register by internal participation rather than gap presence alone
Quality scoring: Combines participation concentration and sigma displacement into a single register score
Mitigation tracking: Continuously estimates how much of each register has been repaired by later price action
Automatic lifecycle retirement: Fully mitigated or invalidated zones can be retired automatically to reduce clutter
Internal histogram bars: Optional profile bars show where lower-timeframe participation concentrated inside the zone
Point-of-control line: Each register maintains a local participation midpoint for tactical reference
Midline support: Optional dotted midpoint line helps visualize the fair center of the register
Dashboard summary: Displays bull count, bear count, mitigated count, average quality, best quality, stack count, and bias
Data-window exports: Publishes stack bias, quality sum, and active register count for downstream reading
Visual Elements
Register boxes: The outer body of each imbalance zone shows whether price is dealing with bullish or bearish open inefficiency
Participation bars: Optional internal profile bars highlight where lower-timeframe participation concentrated inside the register
Midline and POC references: The centerline and participation high point help identify the most important sub-levels inside the zone
Adaptive edge intensity: Stronger registers receive more visual emphasis than weaker ones
Mitigation labels: Each register updates from open to mitigation to filled so the chart communicates lifecycle state directly
Best Practices
Use the register stack as context, then let your own execution model decide entries
Favor high-quality registers that align with broader structure instead of reacting to every new zone
Treat partial mitigation as a sign that some imbalance has already been repaired, not as automatic invalidation
Be especially careful on symbols with poor lower-timeframe data because internal participation quality can degrade
If the active stack flips from one side to the other quickly, read that as changing imbalance context rather than a guaranteed reversal signal
Input Parameters
Intrabar Data:
Auto Lower Timeframe: Automatically derives a lower timeframe for participation analysis
Custom Lower Timeframe: Allows manual lower-timeframe selection when auto mode is disabled
Calculation Depth: Controls how much lower-timeframe history is requested
Imbalance Detection:
Gap Sigma Filter: Sets the minimum displacement strength required for a new register
Participation Bins: Controls how many internal profile slices are built inside each zone
Max Active Registers: Limits how many open registers remain on the chart at once
Retire Fully Mitigated Zones: Removes zones once they are effectively repaired or invalidated
Lifecycle And Display:
Extend Active Zones: Extends open registers to the right for forward reference
Show Participation Histogram: Displays the internal lower-timeframe bar profile
Show Midline: Draws a dotted centerline through each register
Show Dashboard: Enables the top-right summary panel
How to Use This Indicator
Step 1: Read the Stack Bias
Start with the dashboard. Compare the bullish and bearish active register counts and note the stack bias value. A positive bias means bullish imbalance is dominating the active structure. A negative bias means bearish imbalance is dominating.
Step 2: Focus on Quality, Not Quantity
Use the average and strongest quality readings to judge whether the active stack is meaningful. A chart with fewer but stronger registers is often more actionable than a chart with many weak inefficiencies.
Step 3: Watch Mitigation Progress
Each active register updates from open to partial mitigation to filled. Open registers represent unresolved inefficiency. Deeply mitigated registers have already lost part of their tactical edge.
Step 4: Use The Internal Profile
When the participation histogram is enabled, look for bins that concentrated most of the intrabar volume. The local point of control and denser profile segments often become the most useful retest references inside the wider zone.
Step 5: Apply It As Context, Not A Standalone Trigger
Aperture Imbalance Register works best as a context layer. It helps frame whether an imbalance stack is supporting continuation or warning of unresolved opposing pressure. Use it with your own structure, execution, and risk model.
Indicator Limitations
Because the script uses lower-timeframe data requests, realtime behavior can differ slightly from historical behavior as new intrabars accumulate inside the live bar
Mitigation does not guarantee reversal or continuation. It only shows how much of the zone has been traded back through
A strong register can still fail if broader market structure, liquidity, or volatility conditions change
On very low-history charts or symbols with thin lower-timeframe data, participation quality can be less informative than on liquid instruments
Originality Statement
Aperture Imbalance Register is original in the way it treats imbalances as managed registers rather than passive boxes. The script is published because it contributes more than a generic fair value gap mashup:
It ranks each imbalance with a lower-timeframe participation model instead of drawing every gap with equal importance
It combines gap displacement, intrabar participation, mitigation tracking, and internal histogram rendering into a single workflow
It maintains a tactical register stack with lifecycle management rather than leaving stale zones permanently on the chart
It exposes stack-level information through a dashboard and data-window fields so the indicator can be read systematically
Disclaimer
This indicator is provided for educational and informational purposes only. It is not financial advice or a recommendation to buy or sell any financial instrument. Imbalance zones are analytical references based on historical price behavior and lower-timeframe participation, not guarantees of future reaction. Markets can rebalance, ignore, or invalidate any zone without warning. Always use proper risk management and independent judgment.
-Made with passion by jackofalltrades
Penunjuk
Session Reclaim Planner [AGPro Series]Session Reclaim Planner
🧠 Core Idea
Did price reclaim a key session high or low with enough acceptance to create a valid planning context?
📌 Overview / What it does
Session Reclaim Planner is an intraday decision-support tool built around session high and session low reclaim behavior. It builds a configurable reference session, maps the session high/low rails, then monitors whether price temporarily loses one of those rails and reclaims it with measurable acceptance.
The script produces a 0-100 Reclaim Score, session level rails, a reclaim pocket, a risk edge, a target corridor, event labels, alerts, and a compact AG Pro planning panel. It is designed to help traders organize session reclaim context instead of reacting to every touch of a session level.
It does not predict price direction, automate trades, or mark every session high/low as important. The script focuses on a specific sequence: session rail built -> rail temporarily lost -> rail reclaimed by close -> acceptance quality reviewed.
🎯 Purpose & Design Philosophy
This script was built to fill the gap between simple session level markers and broad session reaction tools.
Many session indicators show highs, lows, opens, boxes, or kill zones. Those references can be useful, but they often leave the trader with the harder question: did the level actually get reclaimed with enough structure to matter?
Session Reclaim Planner supports a planning-first mindset. It asks whether the setup is valid, how strong it is, where the risk edge sits, where the target corridor is, and what the next action state should be.
⚡ Why This Script Is Different
Most session tools focus on time windows, session opens, or static high/low levels.
This script does NOT clone Session Reaction Map, Kill Zone Session Engine, Session VWAP Reaction Engine, Session Range Expansion Planner, Previous Day Sweep & Reclaim, or a generic support/resistance map.
Instead, it focuses only on session rail reclaim behavior after a completed reference session. The reclaim must come from a clear rail loss and a close back through the level, then the script evaluates acceptance, participation, room, and risk structure.
⚙️ Methodology
1. Context Detection
The script builds a configurable session range and stores the session high and low as active reclaim rails.
2. Reference Mapping
The high and low rails are projected forward. The user can evaluate both rails or focus only on the high or low.
3. Reaction Evaluation
The planner waits for a temporary rail loss, then checks whether price closes back through the rail with enough reclaim distance.
4. Visual Output
Accepted events create a reclaim pocket, risk edge, target corridor, chart labels, panel state, and alert conditions.
🗺️ How to Read the Chart
Zones = the reclaim pocket and target corridor.
Labels = rail loss, reclaim watch, plan review, failed reclaim, and target review events.
Colors = bullish low reclaim uses AGPro teal, bearish high reclaim uses AGPro pink, neutral review states use gold, and target context uses indigo.
Panel = current session level, Reclaim Score, acceptance status, risk edge, and action state.
🚦 Signals & States
• Reclaim Watch → price has temporarily lost a selected session rail and the planner is waiting for a reclaim close.
• Acceptance Watch → a reclaim close exists, but the plan still needs enough quality or acceptance.
• Plan Review → score and acceptance are strong enough to review risk and target context.
• Risk Edge Test → price is testing the active risk boundary.
• Failed Reclaim → price closes through the risk edge and the reclaim plan is no longer valid.
• Target Review → price reaches the target corridor and the reaction should be reviewed.
🔔 Alerts Logic
Bullish Session Reclaim triggers when the session low is lost, reclaimed, and the score reaches the alert threshold.
Bearish Session Reclaim triggers when the session high is lost, reclaimed, and the score reaches the alert threshold.
Plan Review triggers when the active reclaim reaches the required score and acceptance conditions.
Failed Reclaim triggers when price closes through the active risk edge.
Target Review triggers when price reaches the active target corridor.
Alerts are attention markers, not trade instructions.
🧩 Confluence Logic
The score combines multiple conditions:
• Reclaim close strength
• Acceptance closes
• Volume support
• Risk-to-target room
• Session range fit
When those elements align, the reclaim context becomes stronger. When one or more elements are weak, the panel keeps the user in watch or no-review states.
📊 When to Use
• 1H publication charts and lower intraday execution-review charts
• Intraday markets with clear session behavior
• Session high/low reclaim workflows
• London or New York continuation/reversal review
• Markets where traders actively monitor session rails
• Clean reclaim sequences after temporary level loss
⚠️ When NOT to Use
• Very low liquidity markets
• Extremely noisy micro timeframes
• Symbols where session windows are not meaningful
• Conditions with erratic gaps or unreliable volume
• Markets where the reference session is not relevant to your workflow
🎛️ Key Inputs
• Visual Timeframe Preset → default chart objects are optimized for 1H and lower publication charts, while 4H or all intraday visuals can be enabled manually.
• Session Timezone → defines how session windows are interpreted.
• Level Build Session → builds the reference high and low rails.
• Monitor Session → defines when reclaim behavior is evaluated.
• Reclaim Rail Mode → selects high, low, or both rails.
• Minimum Rail Loss ATR → controls how much level loss is required before a reclaim watch starts.
• Acceptance Closes → controls how many closes must hold the reclaimed side.
• Target Corridor Model → selects rail-based, R-based, or hybrid target logic.
• Panel and Label Settings → control readability, location, theme, and font sizes.
🖥️ Interface & Visual Design
The interface is built around a clean AG Pro planning panel and chart-first visual structure.
The session rails define the level context. The reclaim pocket defines the recovered area. The risk edge shows where the active plan weakens. The target corridor frames the next review area.
Labels are intentionally compact and offset away from candles so the chart remains readable without looking empty.
🧪 Practical Usage Workflow
1. Read the AG Pro panel.
2. Check whether the session rails are built.
3. Wait for a rail loss and reclaim close.
4. Review the Reclaim Score and acceptance count.
5. Compare the risk edge and target corridor with broader market context.
🔍 Interpretation Guidelines
Treat the script as a structured session reclaim map.
A higher score means the reclaim has cleaner acceptance, better participation, and better room relative to risk. A lower score means the reclaim may still exist, but the plan quality is weaker or incomplete.
The target corridor is a review area, not a guaranteed objective.
🚫 What This Script Is NOT
• Not a prediction engine
• Not financial advice
• Not auto trading
• Not guaranteed signals
• Not a generic support/resistance map
• Not a session open reaction scanner
• Not a VWAP reclaim tool
⚠️ Limitations & Transparency
Session behavior depends heavily on symbol, liquidity, timezone, and timeframe.
A reclaim that looks clean on one timeframe may look incomplete or noisy on another.
Volume support can be less reliable on markets where reported volume is limited or synthetic.
No rule-based script can account for every news event, spread condition, execution constraint, or market regime shift.
🧠 Market Context Notes
Session reclaim behavior often matters because traders watch session highs and lows as liquidity and structure references.
The key distinction is not the level itself. The key distinction is whether price lost the level, reclaimed it, and then held acceptance strongly enough to deserve review.
🧾 Use Case Examples
When price sweeps below the built session low, closes back above it, holds acceptance, and has room toward the opposite rail, the panel may move into Plan Review.
When price reclaims a rail but immediately closes through the risk edge, the state shifts to Failed Reclaim.
When price reaches the target corridor, the script marks Target Review so the user can evaluate the reaction instead of assuming continuation.
🧱 System Philosophy
Session Reclaim Planner follows the AGPro decision-engine model:
Validate the setup.
Score the quality.
Map the risk.
Frame the target.
Show the next action state.
🔐 Non-Promise Statement
The script does not provide certainty.
It organizes session reclaim context with rule-based logic and visual planning references.
📉 Risk Disclosure
Trading involves risk.
Users are responsible for their own decisions, risk management, and execution.
This script is for educational and analytical use only and does not provide financial advice.
📚 Educational Note
Use the tool to study how session high and session low reclaim behavior changes across symbols, sessions, and timeframes.
Penunjuk
Mobile Wallstreet Confidence IndicatorMobile Wallstreet Confidence Indicator
Most indicators lie to you. They fire signals on every candle, flood your chart with noise, and leave you holding the bag wondering what went wrong. This one is different.
The Mobile Wallstreet Confidence Indicator was engineered to stay silent until the market is genuinely ready — and when it fires, you'll know exactly why and exactly how confident the setup is.
HOW IT WORKS
Every signal passes through a strict 6-layer filter system before a single arrow appears on your chart:
1. Multi-Timeframe Stack (M15 / H1 / H4 / D1)
The indicator reads all four timeframes simultaneously using a triple EMA alignment model. You control how many must agree before a signal is even considered. No more trading against the higher timeframe trend.
2. Hull MA Momentum Gate
Price must be on the correct side of a rising or falling Hull MA. If momentum isn't confirmed, the signal is blocked — full stop.
3. ATR Depth & Range Filter
The market must show meaningful range and retrace depth relative to ATR. Flat, choppy, low-conviction price action gets filtered out automatically.
4. Structure Clearance
Signals won't fire into overhead resistance or below key support. The indicator measures structure clearance in ATR units so it adapts to every market and every volatility environment.
5. Pattern Rank (0–10)
Each setup is scored across 5 criteria — EMA alignment, RSI momentum, structure break, candle body strength, and price position. Only setups above your minimum rank threshold make the cut.
6. Confidence Score (0–100)
Every signal comes with a live confidence score weighted across MTF agreement, trend alignment, Hull momentum, RSI strength, and pattern rank. You see the number. You decide your conviction.
WHAT YOU GET ON THE CHART
🟢 BUY arrow — all layers aligned bullish, confidence threshold met
🔴 SELL arrow — all layers aligned bearish, confidence threshold met
📊 MTF Dashboard — live top-right panel showing M15 / H1 / H4 / D1 direction, bull/bear counts, confidence scores, pattern ranks, and a plain-English status message telling you exactly what the market is waiting on
🏷️ Signal Labels — confidence score and pattern rank printed directly on every arrow so you never have to guess signal quality
FULLY CUSTOMIZABLE
Every parameter is adjustable to fit your trading style:
Execution timeframe
Fast / Slow EMA periods
Hull MA period
ATR period
Number of MTF timeframes required to agree
Minimum confidence score threshold
Minimum pattern rank threshold
Retrace depth multiplier
Structure clearance multiplier
Structure lookback window
Toggle new signals only, labels, and dashboard on/off
BUILT-IN ALERTS
Set TradingView alerts on BUY and SELL signals and never miss a setup — whether you're watching the screen or not.
WHO THIS IS FOR
This indicator is for traders who are done with noise. If you want a tool that thinks before it speaks, filters relentlessly, and gives you full transparency on every signal it generates — this was built for you.
Swing traders. Day traders. Multi-timeframe operators. Anyone who trades with a plan.
Mobile Wallstreet. Confidence on every candle. Penunjuk
Confluence Engine Strategy [JOAT]Confluence Engine Strategy
Overview
Confluence Engine Strategy is a fully automated Pine Script v6 strategy that combines four independent signal layers into a single numeric confluence score (0–100) before executing any trade. Entries require genuine agreement between linear regression momentum, dual EMA trend regime, ATR volatility state, and higher-timeframe bias. All exits are ATR-proportional with configurable take-profit and stop-loss multiples, plus a bar-based timeout and a trend-flip emergency exit. Commission (0.05% per side) and slippage (2 ticks) are configured for realistic backtesting.
Why Require Confluence?
Single-condition strategies (e.g., "go long when RSI crosses 50") produce entries in every conceivable market environment — ranging, trending, low-volatility, high-volatility — most of which are statistically unfavourable for that signal type. Requiring multiple independent conditions to agree simultaneously filters the entry universe down to the high-probability subset where each individual indicator is operating in its most favourable context. The Confluence Engine makes this filtering explicit and auditable through a numeric score.
Signal Layer 1 — Linear Regression Crossover
The primary entry trigger mirrors the Regression Flux Candles logic: a 21-bar linear regression of close (LR close) crossing above/below an 8-bar SMA of itself. The LR approach de-noises price before computing the crossover, significantly reducing the whipsaw rate compared to raw close-based SMA crossovers.
Signal Layer 2 — Dual EMA Trend Regime
Two exponential moving averages (fast: 21-period, slow: 55-period) define the trend regime. Long entries are only considered when the fast EMA is above the slow EMA; short entries only when fast is below slow. This prevents the LR crossover from triggering counter-trend entries in established trends — one of the most common sources of false signals in momentum strategies.
Signal Layer 3 — ATR Volatility State
The current 14-bar ATR is compared to a 50-bar ATR. Entries are only accepted when the current ATR is above a configurable fraction of the slow ATR (default 0.7). This volatility gate blocks trades during compression phases — low-volatility periods where breakouts frequently fail. The strategy only participates when directional energy is present.
Signal Layer 4 — Higher-Timeframe Bias
A higher-timeframe linear regression direction is fetched via request.security() with lookahead_off. The HTF LR close vs. HTF LR open comparison gives a single bullish/bearish vote from the higher timeframe. Long entries receive a confluence bonus when the HTF agrees; short entries receive a bonus when the HTF is bearish. This aligns trade direction with the prevailing macro bias.
Confluence Score and Threshold
Each of the four layers contributes points to the confluence score:
- LR crossover in direction: +30
- Dual EMA alignment: +25
- ATR volatility expansion: +20
- HTF bias alignment: +25
Maximum score: 100. The minimum required score to execute an entry (default 60) filters out entries where fewer than three layers agree. This threshold is adjustable — lower it for more signals, raise it for higher selectivity.
Entry Logic
Long: LR crossover up AND the accumulated confluence score >= minimum AND the signal is on a confirmed bar AND warmup has elapsed AND no position is currently open AND no cooldown bars remain.
Short: LR crossover down AND confluence >= minimum AND same guards.
A configurable cooldown period (default 5 bars) prevents re-entering the same direction immediately after an exit, avoiding overtrading in choppy conditions.
Exit Logic — Four Exit Conditions
1. ATR Take-Profit: Long exits when close >= entry + ATR × TP multiplier (default 2.0). Short exits below entry - ATR × TP.
2. ATR Stop-Loss: Long exits when close <= entry - ATR × SL multiplier (default 1.2). Short exits above entry + ATR × SL.
3. Bar Timeout: If neither TP nor SL is hit within a configurable number of bars (default 20), the trade exits at market — preventing capital from being locked in stalled trades.
4. Trend Flip Exit: If the dual EMA regime flips against the trade direction (fast EMA crosses slow EMA), the trade exits immediately — recognising that the structural basis for the entry has been invalidated.
Strategy Properties
- Initial capital: $10,000
- Order size: 10% of equity per trade (sustainable risk allocation)
- Commission: 0.05% per side (representative of major exchange fees)
- Slippage: 2 ticks (accounts for spread and execution delay)
- Currency: USD
- Pyramiding: disabled (one position at a time)
These settings are designed to produce realistic backtesting results. Risk per trade is capped well below the 5–10% equity guideline. Commission and slippage are included to prevent overstating performance.
Inputs Reference
Signal Layers
- LR Length (21) — linear regression period
- Signal SMA Length (8) — crossover trigger SMA
- Fast EMA (21) / Slow EMA (55) — trend regime definition
- ATR Length (14) / ATR Slow Length (50) / ATR Threshold (0.70)
- HTF Timeframe — higher-timeframe bias source (default "D")
Confluence & Filters
- Min Confluence Score (60) — minimum sum of layer scores required for entry
- Cooldown Bars (5) — bars to wait after exit before re-entering
- Max Bars in Trade (20) — timeout exit
Risk Management
- TP ATR Multiple (2.0) — take-profit distance in ATR units
- SL ATR Multiple (1.2) — stop-loss distance in ATR units
How to Read the Results
Apply the strategy to a liquid instrument on a 1H or 4H chart with sufficient history to generate 100+ trades. Evaluate:
- Net profit relative to max drawdown (seek ratio > 2:1)
- Win rate in context of average win vs. average loss
- Profit factor (total gross profit / total gross loss, seek > 1.3)
- Number of trades (sufficient sample size for statistical inference)
Adjust the confluence minimum score to trade off signal frequency against quality: 50 produces more trades, 75 produces fewer but higher-quality entries.
Non-Repainting Design
All entries fire on strategy.entry() within barstate.isconfirmed blocks. HTF bias uses lookahead_off. No future bar data is accessed. Historical signals do not shift position.
Limitations
- The strategy is designed as a general-purpose framework. It is not optimised for any specific instrument or session. Optimal parameters vary significantly across markets and timeframes.
- ATR-based exits are approximate. In gap markets (equities overnight, weekend gaps on crypto), the stop-loss may be exceeded significantly before the exit executes.
- Backtesting results are computed on historical data only and do not account for execution quality, broker-specific fees, or market impact. Past backtesting performance does not guarantee future live results.
- The bar timeout exit may prematurely close positions that would have eventually reached TP. This is a deliberate conservative design choice to limit capital lock-up, not a flaw.
Disclaimer
This strategy is provided for educational and informational purposes only. Backtesting results presented in the strategy tester represent historical simulation and do not guarantee any future trading outcome. Past performance is not indicative of future results. Never risk capital you cannot afford to lose. Always use proper risk management and conduct independent analysis before making any trading decisions.
Made with passion by officialjackofalltrades
Strategi
Prism Channel Architecture [JOAT]Prism Channel Architecture
Introduction
Prism Channel Architecture is a dual-channel overlay indicator that layers two mathematically distinct structural frameworks onto your price chart simultaneously: a best-fit Pivot Channel derived from actual price pivot points, and a Linear Regression Channel built from statistical least-squares fitting. Together they create a structural prism through which trend direction, channel quality, and breakout momentum can be evaluated from multiple angles at once.
Most channel tools force you to choose between objectivity and responsiveness. Pivot channels adapt to real market structure but can lag. Regression channels are statistically rigorous but ignore actual swing highs and lows. PCA runs both engines in parallel and highlights the moments when they agree — bull alignment and bear alignment states — as the highest-conviction reads in the system.
Core Concepts
Pivot Channel Fitting
The indicator collects up to a configurable maximum of confirmed pivot highs and pivot lows using TradingView's built-in pivot functions:
float pivHigh = ta.pivothigh(high, pivLeft, pivRight)
float pivLow = ta.pivotlow( low, pivLeft, pivRight)
From those stored pivot arrays, it searches for the best pair of recent pivot highs to fit the upper channel boundary, and the best pair of recent pivot lows to fit the lower channel boundary. The quality score for each candidate pair is computed by checking how many of the recent bars were actually contained below the upper line (or above the lower line) within an ATR tolerance:
for k = 0 to checks - 1
float lineY = linePrice(x2, y2, x1, y1, bar_index - k)
if high <= lineY + atrVal * 0.3
contained += 1
float q = safeDiv(float(contained), float(checks), 0.0)
The pair with the highest containment ratio wins and becomes the drawn channel. This means the upper channel line is always the tightest valid resistance line through recent pivot highs, not an arbitrary parallel projection.
Linear Regression Channel
The regression channel computes a full manual least-squares fit over the lookback window, producing slope, intercept, and residual standard deviation:
float slope = safeDiv(n * sumXY - sumX * sumY, n * sumXSq - sumX * sumX, 0.0)
float intc = safeDiv(sumY - slope * sumX, n, close)
float stdDev = math.sqrt(safeDiv(ssRes, n, 0.0))
The upper and lower bands are drawn at `stdDev × Deviation Multiplier` distance from the regression midline, giving bands that are statistically calibrated to the actual spread of price around the trend. Color shifts from bull to bear when slope changes sign.
Channel Alignment Confluence
The system declares a Bull Alignment when both channels simultaneously agree price is in a bullish position — the regression slope is rising AND price is above the regression midline, AND price is in the upper half of the pivot channel (between the midline and the upper band):
bool lrBull = close > midNow and slope > 0.0
bool pivBull = close > uMid and close < uNow
bool alignBull = lrBull and pivBull
This confluence state is highlighted with a subtle background color — a quiet but meaningful signal that two independent structural frameworks are pointing in the same direction.
ATR-Based Breakout Detection
Breakout signals fire when price moves more than a configurable ATR multiple beyond the prior bar, provided the regression slope confirms direction:
bool brkUp = ta.crossover(close, close + crossTol * atrVal) and lrSlope > 0.0
bool brkDn = ta.crossunder(close, close - crossTol * atrVal) and lrSlope < 0.0
Breakout labels (▲ BRK / ▼ BRK) appear above or below the breakout bar and are alert-enabled.
Features
Pivot Channel — best-fit upper/lower boundaries through recent pivot highs/lows, quality-scored by containment ratio
Regression Channel — least-squares midline with statistically calibrated deviation bands, auto-colored by slope direction
Channel midline — dashed neutral midline bisecting the pivot channel for zone positioning
Bull and Bear Alignment detection — background highlight when both channels agree on direction
ATR-normalized breakout labels — ▲ BRK and ▼ BRK when price breaks out with trend confirmation
Channel Quality score — displayed in dashboard as percentage of recent bars contained
Pivot position classification — Bull Zone (upper half) or Bear Zone (lower half)
Up to 40 pivot highs and 40 pivot lows stored and evaluated
10-bar channel projection extended to the right of the last bar
Dashboard: LR direction, deviation mult, pivot quality, pivot position, alignment, breakout, ATR, pivot count
Alerts for bullish breakout, bearish breakout, bull alignment, and bear alignment
Webhook JSON alert format
Watermark
Input Parameters
Pivot Channel
Pivot Lookback Left — bars to the left required to confirm a pivot high or low (default 10)
Pivot Lookback Right — bars to the right required to confirm a pivot high or low (default 5)
Max Pivots Stored — maximum number of pivot highs and lows held in memory (default 30)
Quality Check Length — number of recent bars used to score channel containment (default 20)
Breakout ATR Mult — ATR multiplier threshold for breakout label generation (default 1.5)
Show Pivot Channel — toggle the pivot channel lines on/off
Regression Channel
Regression Length — bars used in the least-squares fit (default 50)
Deviation Mult — standard deviation multiplier for band width (default 2.0)
Show Regression Channel — toggle the regression channel lines and fill on/off
ATR Settings
ATR Length — lookback for ATR calculation used in breakout detection and containment tolerance (default 14)
Visuals
Bull Color — color for uptrending channels and bullish labels
Bear Color — color for downtrending channels and bearish labels
Neutral Color — color for channel midlines and neutral dashboard text
Show Dashboard — compact structural summary panel
Show Watermark
Show Breakout Labels — toggle ▲ BRK / ▼ BRK label markers
Alerts
Webhook JSON Format — switches alert messages to JSON format for automation pipelines
How to Use
Add PCA to your chart as a main-pane overlay indicator.
Let the chart load enough history so both channels initialize. A warmup period of at least 60 bars is enforced before channels begin drawing.
Use the Regression Channel to assess macro trend direction. If the midline slope is rising and price is above it, the macro environment is bullish.
Use the Pivot Channel to identify the structural support and resistance boundaries formed by actual price pivots. The upper pivot line is the tightest valid resistance. The lower pivot line is the strongest structural support.
Watch for Bull Alignment (cyan background) when both systems agree price is in a bullish structural position. This is the highest-conviction environment for long setups.
Watch for Bear Alignment (red background) for bearish structural setups.
Treat Breakout labels as momentum confirmation signals — they only fire when an ATR-significant price move occurs in the direction of the regression slope.
Check the Pivot Quality score in the dashboard. A quality above 65% means the channels are actively containing price well. Below 40% means the channel fit is loose and breakouts are less reliable.
Indicator Limitations
Pivot channel fitting evaluates only the 8 most recent pivot highs and the 8 most recent pivot lows when searching for the best pair. In very choppy markets with many closely-spaced pivots, the fitted channel may appear narrow or erratic.
The regression channel is recalculated on every bar over a fixed lookback window. It will repaint the past visually as new bars are added — the channel reflects the lookback window ending at the current bar, not a fixed historical period.
Channel quality scores can be artificially high in low-volatility trending conditions where price barely touches the edges of the channel.
Breakout signals require both an ATR threshold move AND a confirming regression slope. In sideways markets the slope condition filters out most breakout candidates, which may lead to missed signals on genuine horizontal range breaks.
Originality Statement
Prism Channel Architecture is an original Pine Script v6 publication. The dual-engine architecture combining a quality-scored best-fit pivot channel with an independently computed least-squares regression channel, and the definition of alignment confluence as agreement between those two distinct structural systems, is an original design. The pivot quality scoring methodology — measuring the containment ratio of recent bars within the candidate channel bounds with ATR tolerance — is an original technique not derived from any existing published indicator.
Disclaimer
This indicator is for educational and informational purposes only. Channels, alignment states, and breakout labels are analytical tools and do not constitute financial advice. Channel boundaries can and will be violated without warning. Always apply proper risk management and never trade solely based on indicator signals.
-Made with passion by jackofalltrades
Penunjuk
