AetherEdge - TIDE | Flow + RL Oscillator🖊️ Overview
AE-TIDE is a lower-panel oscillator measuring participation-weighted money flow and its excess — the "Overflow" of one-sided activity. Where most flow tools simply display that excess, AE-TIDE adds a reinforcement-learning agent that learns, from realized outcomes, whether fading an Overflow exhaustion actually leads to a reversal in this market. It also scores every divergence with a Bayesian posterior, automatically down-weighting the divergences that do not work. It is a flow oscillator that gets smarter per market rather than relying on fixed thresholds.
🔶 Key Features
Participation-weighted Money Flow ( ) plus an Overflow band for one-sided extremes
A fast Hyperwave momentum line for early shifts in drive
An RL (tabular Q-learning) agent that learns when fading exhaustion pays, firing reversal signals only then
Beta-Bernoulli online reliability scoring for divergences — each one shows a learned reliability %
Divergences below relGate are hidden automatically
Gold-framed HUD; no repaint — every signal gates on bar close
🧠 Technical Architecture
Flow: impulse = (ATR-normalized return) × (relative volume), EMA-smoothed and z-scored into a Money Flow; the part beyond ± threshold is the Overflow. Hyperwave is the same normalization on a short EMA.
RL (Q-learning, TD(0)): state = flow regime (overflow side ×3 × momentum slope ×2 = 6 states), actions = {wait, fade}. The fade reward is the realized return conditioned on the overflow side at the moment the fade was taken (fade an overbought flow → rewarded if price falls). Update Q(s,a) ← Q + α ; the fade action is optimistically initialized to guarantee exploration. A signal fires only when fade-value > 0 (learned to pay) and an Overflow exhaustion triggers.
Bayesian divergences: regular divergences are detected on oscillator pivots; each (side × extreme) bucket holds a Beta(a, b) posterior, updated by the realized outcome divK bars later. The displayed reliability is the posterior mean.
Honest scope: classic tabular Q-learning plus Beta-Bernoulli estimation — not deep RL, not a crystal ball.
⚙️ Recommended Settings & Tuning Guide
Key parameters: ofThr (Overflow threshold), rlAlpha / rlGamma / warmup, divK (outcome horizon), relGate (minimum reliability to show).
Raise ofThr → stricter overflow (suits alts); lower → more sensitive
Crypto starting points (tune on your chart):
BTC / ETH (1H–4H): defaults are the baseline (ofThr = 30)
SOL / XRP and high-vol alts: wicky and spiky — ofThr = 35–40, relGate = 0.6 for proven divergences only
Scalping (5–15m): shorter hwLen, divK = 5–8 for quick verdicts
Swing (daily): divK = 15–20, longer warmup so the agent learns enough
The RL needs time to learn a market's character; in trending markets fade signals thin out automatically (correct behavior)
💡 How to Use in Practice
FADE signals: appear only when Overflow recedes from an extreme AND the agent has learned that fading pays in this regime — use as a reversal trigger
Reading Overflow: a bright color is excessive one-sided participation; when it stalls or recedes, that exhaustion often precedes a reversal
Reliability-scored divergences: readings above ~70% mark contexts that historically reversed; ~50% means stand aside
Multi-timeframe: combine higher-timeframe flow direction with lower-timeframe FADE entries
Combinations: pair AE-TIDE's exhaustion fades with directional signals from AE-QUORUM or AE-KALMAN to separate trend pullbacks from range reversals
⚠️ Important Notes
Learning period: no FADE signals appear until the Q-learning agent spins up (warmup bars) — this is by design
Reliability starts at 50%: each divergence bucket sits near neutral until its posterior accumulates enough samples
Learning reset: changing inputs, symbol, or timeframe re-learns the internal state
Fading is countertrend: fading a strong trend too early is dangerous; even when the agent suppresses it, the final call is yours
🚨 Disclaimer
This indicator is for educational and informational purposes only and is not financial advice or a recommendation to buy or sell. No method guarantees future profits; past performance does not indicate future results, and trading carries the risk of loss. All trading decisions are your own — use proper backtesting and disciplined risk management. Indicateur
AetherEdge - Adaptive Trend Bandit🖊️ Overview
AE-ATB is an adaptive SuperTrend whose ATR multiplier is chosen by a learning bandit. A fixed-multiplier SuperTrend is too tight in calm markets and too loose in volatile ones. AE-ATB first discovers volatility regimes with online k-means, then a contextual bandit (UCB) learns which ATR multiplier has actually paid in each regime. It does not just switch the multiplier with volatility — it learns the best one from reward.
🔶 Key Features
Streaming k-means sorts relative volatility into calm / normal / volatile regimes (not hard-coded thresholds)
A contextual multi-armed bandit (UCB) learns the best ATR multiplier per regime from realized return
A time-varying adaptive SuperTrend that tightens or widens by regime automatically
Direction-colored line and fill, with BUY/SELL signals on trend flips
A gold HUD showing trend, volatility regime, selected multiplier, learned best multiplier, arm value, and pull count
Deterministic exploration (UCB) — identical across reloads, no repaint
🧠 Technical Architecture
k-means (unsupervised): relative volatility = ATR / SMA(ATR) is the feature; three centroids update by competitive learning (only the winning centroid moves, c += lr·(x − c)). Centroid order ranks calm/normal/volatile.
UCB bandit (RL): candidate ATR multipliers (base, base+step, …) are the arms and the volatility cluster is the context. Each (context, arm) value Q is an incremental mean; selection is UCB1: argmax(Q + c·√(ln(total pulls)/pulls)), prioritizing untried arms while balancing exploration and exploitation. Reward = held direction × realized return (ATR units), so multipliers that kept us on the right side of the move score higher.
Adaptive SuperTrend: standard bands = hl2 ± (selected multiplier × ATR), updated each bar with the selected multiplier; direction flips on a break of the active band.
Honest scope: online k-means plus a UCB contextual bandit. SuperTrend is a public concept; this is not a neural network and not a crystal ball.
⚙️ Recommended Settings & Tuning Guide
Key parameters: ATR length, volatility baseline length, multiplier base/step/count, ucbC (exploration), warmup.
Raise ucbC → more exploration (tries more multipliers); lower → more exploitation (sticks to the learned best)
Match the multiplier range (base … base + step×(count−1)) to the instrument's volatility character
Crypto starting points (tune on your chart):
BTC / ETH (1H–4H): defaults are the baseline (base 1.5, step 0.5, 5 arms)
SOL / XRP and high-vol alts: base 2.0 / step 0.5 for a wider range to avoid wick stop-outs
Scalping (5–15m): shorter ATR length, slightly tighter multiplier range
Swing (daily): wider multiplier range, longer warmup so each regime is learned
Right after a new regime appears, behavior is unsettled until each multiplier has been tried once (UCB exploration)
💡 How to Use in Practice
Trend-following: ride the line color and BUY/SELL; a larger multiplier means a roomier trail, a smaller one a tighter trail
Reading the regime: in VOLATILE the multiplier widens to avoid fakeout stop-outs; in CALM it tightens to get on board sooner — automatic adaptation
Best-multiplier panel: shows the learned best multiplier for the current regime, useful as a manual-trail reference
Multi-timeframe: higher-timeframe AE-ATB for the trend, lower for timing
Combinations: pair with AE-QUORUM's directional probability or AE-VECTOR's target band, and let AE-ATB's trail run the winner
⚠️ Important Notes
Learning period: no signals fire until warmup bars; the bandit needs time to learn each regime's multiplier
Learning reset: changing inputs, symbol, or timeframe re-learns the centroids and arm values
Multiplier moves while exploring: early on the multiplier shifts and the adaptive SuperTrend can jump or whipsaw (it settles as pulls accumulate)
Trend-following's nature: in ranges it can suffer repeated stop-outs — use the regime read and position sizing together
🚨 Disclaimer
This indicator is for educational and informational purposes only and is not financial advice or a recommendation to buy or sell. No method guarantees future profits; past performance does not indicate future results, and trading carries the risk of loss. All trading decisions are your own — use proper backtesting and disciplined risk management. Indicateur
AetherEdge - VECTOR | Conformal Forecast🖊️ Overview
AE-VECTOR forecasts the move over the next H bars and attaches a calibrated prediction interval to the target. A point estimate alone cannot be trusted or sized. AE-VECTOR learns the expected move with online regression and uses conformal prediction to draw a band around the target within which the realized value lands roughly 1 − α of the time. Its essence is quantifying the uncertainty of the forecast, not just its center.
🔶 Key Features
Online linear regression that learns the H-bar move (in ATR units) — m̂
A calibrated target band via conformal regression (target ± q·ATR, coverage ≈ 1 − α)
The band is volatility-normalized, so it widens in high vol and tightens in low vol automatically
A target cone at the right edge (projection line + band box + target/coverage label)
A highly selective signal that fires only when decisive (even the pessimistic band end is beyond price)
A gold HUD showing direction, predicted move, target, band width, coverage, and decisiveness
No repaint — signals gate on bar close; labels use the H-bar-lagged realized move
🧠 Technical Architecture
Regression: trend slope, RSI momentum, short momentum, range position, and volatility regime are standardized (EWMA), and a linear model m̂ = w·x + b is trained by SGD (squared loss, L2). The label is the realized H-bar move (ATR units); the current forecast uses no future data.
Conformal target band: the realized absolute residuals of past forecasts (in ATR units, i.e. volatility-normalized) are stored in a rolling calibration set. For a new forecast, the (1 − α) empirical quantile q gives the band target ± q·ATR. By the split (inductive) conformal guarantee, the realized value falls inside this band with coverage calibrated to about 1 − α.
Honest scope: a linear regressor plus inductive conformal prediction — not a neural network, and not a guarantee of the point estimate. What is guaranteed is the band's coverage.
⚙️ Recommended Settings & Tuning Guide
Key parameters: H (horizon), α (band coverage = 1 − α), moveThr (minimum predicted move), lr (learning rate), warmup.
Lower α → wider, higher-coverage band (conservative); higher → tighter band
H: small (5–8) for scalping, large (20–40) for swing
Crypto starting points (tune on your chart):
BTC / ETH (1H–4H): defaults are the baseline (H = 10, α = 0.10)
SOL / XRP and high-vol alts: moveThr ≈ 0.8 to filter small noisy forecasts; α = 0.08 for a slightly wider band
Scalping (5–15m): H = 5–8, lr = 0.02 for fast adaptation
Swing (daily): H = 20–40, raise calibN to stabilize the quantile estimate
Requiring "decisive" narrows to confident targets where even the pessimistic band end favors the trade
💡 How to Use in Practice
As a target: the cone's center line is the target, the band its uncertainty — an objective basis for take-profit levels and R:R
Reading band width: narrow = stable forecast (model confident), wide = uncertain (stand aside or downsize)
Decisive signals: a calibrated, strong condition that the target sits beyond price even pessimistically — useful at the start of a move
What coverage means: a 90% band has historically contained ~90% of realized values — a calibrated expectation
Multi-timeframe: target direction from a higher-timeframe VECTOR, timing on a lower one
Combinations: pair with AE-QUORUM's directional probability or AE-HELM's trade management, and design exits with VECTOR's band
⚠️ Important Notes
Learning period: until both the regression and the calibration spin up (warmup + minCalib bars), the target shows "warming" and no signals fire
Learning reset: changing inputs, symbol, or timeframe re-learns the internal state
The band is guaranteed, not the center: the point estimate can be wrong, and during shocks the band can briefly under-cover
Linear extrapolation has limits: it is weak to sharp regime changes and unforeseen news — treat it as a projection of the current state
🚨 Disclaimer
This indicator is for educational and informational purposes only and is not financial advice or a recommendation to buy or sell. No method guarantees future profits; past performance does not indicate future results, and trading carries the risk of loss. All trading decisions are your own — use proper backtesting and disciplined risk management. Indicateur
AetherEdge - KALMAN | State-Space Trend🖊️ Overview
AE-KALMAN treats price as a noisy observation and recursively estimates the true underlying trend level and velocity (slope) behind it with a two-state Kalman filter. Rather than averaging the past like a moving average, it runs a predict → observe → correct cycle on every bar. Crucially, the filter re-estimates how noisy the market is from its own forecast residuals, so it adapts automatically as volatility shifts. The lag-versus-smoothness trade-off is resolved probabilistically instead of by a fixed setting — that is the essence of AE-KALMAN.
🔶 Key Features
A slope-colored Kalman trend line estimating level and velocity (slope) simultaneously
Predictive bands whose width adapts to the predictive variance S — not a fixed multiplier
Shock detection via a standardized innovation "surprise" z-score — flags moves and regime breaks the model did not expect, with a marker and background tint
Innovation-based adaptive measurement noise — the filter learns the market's noise level from its own residuals and self-tunes (toggle)
A multi-step forecast ray (level + n·slope) with the projected price labeled
A gold-framed HUD showing trend, velocity, surprise z, Kalman gain, band width, noise, and forecast
No repaint — every signal is gated on bar close
Process/measurement noise is ATR-scaled, aligning automatically with each symbol's volatility
🧠 Technical Architecture
The state-space model is a local linear trend. The state vector is x = , with transition F = [ , ] (level advances by slope; slope is a random walk) and observation H = (price = level + measurement noise). Each bar runs the standard recursion:
Predict: level' = level + slope; covariance P' = F·P·Fᵀ + Q
Update: innovation y = price − level'; predictive variance S = P'₁₁ + R; Kalman gain K = P'·Hᵀ / S; state correction x = x' + K·y; covariance P = (I − K·H)·P'
The 2×2 case is implemented in closed form by hand, so it needs no matrix inversion and stays numerically transparent.
Adaptive noise: the observed innovation variance estimates S = P'₁₁ + R, so R ≈ Var(y) − P'₁₁ is tracked online with an EWMA (with a floor). The filter therefore behaves smoothly in quiet conditions and responsively when the market turns turbulent.
Regime adaptation: velocity = slope ÷ ATR is compared against a dead-zone (slopeThr) to classify UP / DOWN / FLAT, while the magnitude of the surprise z = y ÷ √S detects shocks (news, fast moves).
Honest scope: this is a linear-Gaussian state-space filter (Kalman) — not a neural network and not a crystal ball. The forecast is a linear extrapolation of the current state.
⚙️ Recommended Settings & Tuning Guide
The defaults are tuned for crypto. The parameters that matter most are measurement noise (measR), process noise (procLvl / procSlp), band width (bandMult), the flat dead-zone (slopeThr), and the shock threshold (shockThr).
Smoother / slower: raise measR / lower procLvl
Faster / more reactive: raise procLvl / lower measR
procSlp controls how quickly trend direction may change — smaller keeps direction stable
Crypto starting points (tune on your chart):
BTC / ETH (1H–4H): defaults are a solid baseline; raise procLvl toward 0.4 to catch turns faster
SOL / XRP and high-volatility alts: wicky and noisy — use measR 2.0–2.5 and slopeThr 0.03–0.05 to suppress false FLAT/flip reads
Scalping (1–15m): raise procLvl (0.5+) for responsiveness; bandMult 1.5–2.0 for reversion entries
Swing (daily): lower procSlp (0.01–0.02) to stabilize slope; raise measR for a smoother line
For volatile crypto, keep adaptive noise ON; switch it off only when you want a fixed, predictable feel
💡 How to Use in Practice
Trend-following: ride the line color (velocity sign) and the UP/DN signals; treat FLAT as a range/stand-aside state
Mean-reversion: taps of the upper/lower predictive band flag overextension; because band width scales with S, small stretches in low vol and large stretches in high vol are judged on the same footing
S/R flips & breakouts: a decisive close through the Kalman level with a velocity flip marks the start of a regime change
Shock markers: highlight news, liquidations, and fakeouts — useful as an overextension warning or the onset of a volatility expansion
Forecast ray: the extrapolation of current level + velocity, handy for higher-timeframe bias and rough targets
Multi-timeframe: read directional velocity from a higher-timeframe AE-KALMAN and time entries on a lower one; agreement of both line colors is a high-confidence filter
Combinations: pair with AE-STRATA (SMC structure + ML/RL) and act only when Kalman velocity and STRATA's smart-money probability agree
⚠️ Important Notes
Initial convergence: from a large initial uncertainty, the filter takes a few dozen bars to settle — wait for values to stabilize at the start of history or right after switching symbols
Lag vs smoothness is a trade-off: smoother means slower; faster means noisier — there is no universal setting
The forecast is not a guarantee: it is a linear extrapolation (level + n·slope) and will miss sharp turns; treat it as a projection of the current state only
Parameter sensitivity: optimal noise settings vary by timeframe and symbol — always tune on the chart
🚨 Disclaimer
This indicator is provided for educational and informational purposes only and is not financial advice or a recommendation to buy or sell. No method guarantees future profits; past performance does not indicate future results, and trading carries the risk of loss. All trading decisions are your own — please use proper backtesting and disciplined risk management. Indicateur
MACD Pressure Zones | Alpha S+Range Compression Map | Alpha S+
Range Compression Map is a chart-based range and sideways-structure detection tool designed to help users study price compression directly on the chart.
Instead of displaying a separate oscillator or status panel, this script draws volatility-adjusted range boxes around areas where price remains contained inside a controlled structure. The box then changes its border and background state when price breaks above, breaks below, or returns back into the range after a failed break.
The script does not provide entry or exit recommendations. Its purpose is to help users study range compression, sideways structure, breakout context, failed breaks, and the relationship between price action and volatility-adjusted boundaries.
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Core Concept
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Markets often alternate between expansion and compression.
During compression, price tends to remain inside a relatively narrow structure before a directional move develops.
This script uses a volatility-adjusted range model to identify when recent closing prices remain inside an ATR-based boundary around a central price line.
The main concept is:
• calculate a central range reference
• build upper and lower boundaries using ATR-based volatility
• check whether recent closing prices remain inside those boundaries
• draw a range box when price is contained
• keep the visual focus on the box instead of adding many chart labels
• change the box state when price breaks upward or downward
• optionally detect failed breaks when price returns back into the range
• use border and background color changes instead of heavy signal markers
This makes the indicator useful as a chart-based range structure viewer rather than a standalone buy or sell signal tool.
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What This Script Shows
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The script can display:
• range compression boxes
• active sideways structure zones
• volatility-adjusted upper and lower range boundaries
• dotted range midpoint line
• unbroken range state
• upward break state
• downward break state
• optional fakeout state
• optional break labels
• optional fakeout labels
• optional adaptive center mode
• optional top and bottom range lines
These elements are designed to help users identify whether price is still compressed inside a range or has moved outside of the structure.
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How It Works
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1. The script calculates a central price reference using the selected center mode.
2. In SMA mode, the center is based on a moving average of the selected source.
3. In Adaptive mode, the center updates only when price moves far enough from the previous center using an ATR-based step.
4. The script builds an upper and lower range boundary around the center.
5. It checks whether recent closing prices remain inside the volatility-adjusted range.
6. When the selected number of recent bars stays inside the range, the script draws a range compression box.
7. If a new detected range overlaps with an existing box, the structure can be merged instead of creating unnecessary duplicate boxes.
8. While the range remains unbroken, the box stays in its neutral range color.
9. If price closes above the active range boundary, the box changes into an upward break state.
10. If price closes below the active range boundary, the box changes into a downward break state.
11. If fakeout detection is enabled, the script can change the box into a fakeout state when price returns back inside after a break.
12. The midpoint line helps users visually track the center of the detected range structure.
13. Optional labels can be enabled, but the default design keeps the chart clean by using box color states.
This structure helps users study compression, range behavior, breakout context, and failed-break behavior without relying on crowded markers.
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Inputs And Customization
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Users can adjust:
• minimum range length
• range width multiplier
• ATR length
• source price
• center mode: SMA or Adaptive
• adaptive ATR length
• adaptive factor
• overlap merging behavior
• cooldown after break
• maximum active range duration
• trend pause classification using ADX
• break buffer
• body confirmation for break conditions
• fakeout detection
• fakeout window
• midpoint line visibility
• top and bottom range line visibility
• optional break labels
• optional fakeout labels
• range box colors
• break box colors
• fakeout box colors
• border transparency
• background transparency
• border width
• signal border width
The default settings are designed to keep the chart clean while making range structures visible directly on the price chart.
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Visual Elements
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The script includes:
• range box
• midpoint line
• optional range top and bottom lines
• border color state
• background color state
• optional break labels
• optional fakeout labels
The range box is the main visual element.
The midpoint line shows the central level of the detected structure.
The border and background color provide the main state information without requiring large labels.
Optional labels can be enabled for users who prefer explicit text confirmation, but the primary design is based on clean chart boxes.
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Reference States
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Unbroken Range:
Price remains inside the detected volatility-adjusted range. The box stays in its neutral range color.
Upward Break:
Price closes above the active range boundary. The box changes to the upward break color.
Downward Break:
Price closes below the active range boundary. The box changes to the downward break color.
Fakeout:
If fakeout detection is enabled, price breaks out of the range and then returns back inside the structure within the selected fakeout window. The box changes to the fakeout color.
Trend Pause:
When ADX-based classification is enabled, some range structures can be treated as trend-pause zones rather than pure sideways ranges. This can help distinguish quiet consolidation from temporary pauses inside a stronger directional environment.
Adaptive Range:
When Adaptive mode is selected, the center line updates less frequently and only shifts when price moves far enough away from the previous center. This can create a more stable range reference in some market conditions.
These states are informational and should not be interpreted as trading instructions.
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How To Use
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Use this script as a chart-based range structure viewer.
General interpretation examples:
• A neutral range box can help users identify where price is moving inside a controlled sideways or compression structure.
• A green upward-break box can help users review where price moved above the detected range.
• A red downward-break box can help users review where price moved below the detected range.
• A yellow fakeout box, when enabled, can help users study failed range breaks.
• The midpoint line can be used as a visual reference for the center of the range.
• The adaptive center mode can be tested when users want a slower-moving center reference.
• The SMA center mode can be used when users want a more standard range-detection approach.
• Optional labels can be turned on for explicit break text, but the box color state is designed to be the primary visual guide.
This script is best reviewed together with price action, volume, volatility, support and resistance, trend structure, and higher-timeframe context.
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Confirmation And Repainting Notes
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The script uses recent closing prices and ATR-based boundaries to detect range structures.
Range boxes can update as new candles appear.
On realtime candles, values can change before the candle closes because price, ATR, and range conditions can update intrabar.
Break states are based on price moving beyond the active range boundary.
For more conservative analysis, users should evaluate range breaks after candle confirmation.
The script does not use future price data to predict market direction.
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Limitations
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This script does not predict future price movement.
It does not provide entry or exit recommendations.
A range break does not guarantee trend continuation.
A fakeout state does not guarantee reversal.
ATR length, range length, and width multiplier can materially change how often ranges appear.
Very low-liquidity markets, large gaps, news-driven moves, and extreme volatility can reduce the usefulness of range-based analysis.
In strong trending markets, some detected ranges may represent temporary pauses rather than true sideways structures.
This script should not be used as a standalone trading system.
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Disclaimer
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This publication is for educational and informational chart analysis only.
It does not constitute financial advice, investment advice, or a recommendation to trade any financial instrument.
All trading and investment decisions are the responsibility of the user.
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Range Compression Map | Alpha S+
Range Compression Map은 가격이 일정한 변동성 기준 범위 안에서 압축되거나 횡보하는 구조를 차트 위에 직접 표시하는 Range 구조 분석 도구입니다.
별도의 오실레이터나 큰 상태 패널을 중심으로 보여주는 방식이 아니라, 가격이 통제된 범위 안에 머무르는 구간을 박스로 표시하고, 이후 상단 돌파·하단 이탈·Fakeout 상태를 박스의 테두리와 배경색 변화로 구분합니다.
이 스크립트는 진입 또는 청산 추천을 제공하지 않습니다. 목적은 횡보 압축, 박스권 구조, 돌파 컨텍스트, 실패 돌파, 그리고 가격 행동과 변동성 기반 경계 사이의 관계를 분석하는 것입니다.
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핵심 개념
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시장은 확장과 압축을 반복하는 경우가 많습니다.
압축 구간에서는 가격이 비교적 제한된 구조 안에 머물다가 이후 방향성 움직임이 나타날 수 있습니다.
이 스크립트는 중심 가격선을 기준으로 ATR 기반 상단·하단 경계를 만들고, 최근 종가들이 해당 범위 안에 머무르는지를 확인해 Range 구조를 감지합니다.
핵심 개념은 다음과 같습니다.
• 중심 Range 기준선 계산
• ATR 기반 상단·하단 경계 생성
• 최근 종가들이 해당 경계 안에 머무르는지 확인
• 가격이 통제된 범위 안에 있으면 Range 박스 표시
• 많은 라벨보다 박스 자체를 중심으로 시각화
• 상단 돌파 또는 하단 이탈 시 박스 상태 변경
• 선택적으로 돌파 실패 후 Range 안으로 복귀하는 Fakeout 감지
• 무거운 마커 대신 테두리와 배경색 변화 중심으로 표현
이 구조는 단독 매수·매도 신호가 아니라, 차트 위에서 Range 구조를 분석하는 데 적합합니다.
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이 스크립트가 보여주는 것
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이 스크립트는 다음 요소를 표시할 수 있습니다.
• 횡보 압축 박스
• 활성 sideways structure zone
• 변동성 기반 상단·하단 Range 경계
• 점선 중앙선
• 아직 돌파되지 않은 Range 상태
• 상단 돌파 상태
• 하단 이탈 상태
• 선택 가능한 Fakeout 상태
• 선택 가능한 돌파 라벨
• 선택 가능한 Fakeout 라벨
• 선택 가능한 Adaptive Center 모드
• 선택 가능한 상단·하단 Range 라인
이 요소들은 가격이 아직 Range 안에서 압축 중인지, 또는 해당 구조를 벗어났는지를 확인하는 데 도움을 줍니다.
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작동 방식
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1. 스크립트는 선택한 center mode를 기준으로 중심 가격선을 계산합니다.
2. SMA 모드에서는 선택한 기준 가격의 이동평균을 중심선으로 사용합니다.
3. Adaptive 모드에서는 가격이 이전 중심선에서 ATR 기반 기준 이상으로 멀어졌을 때만 중심선이 단계적으로 갱신됩니다.
4. 중심선을 기준으로 상단·하단 Range 경계를 만듭니다.
5. 최근 종가들이 변동성 기반 Range 안에 머무르는지 확인합니다.
6. 설정된 기간 동안 가격이 Range 안에 머무르면 차트 위에 Range Compression 박스를 표시합니다.
7. 새로 감지된 Range가 기존 박스와 겹치면 불필요한 중복 박스를 만들지 않고 병합할 수 있습니다.
8. Range가 돌파되지 않은 동안 박스는 기본 Range 색상으로 유지됩니다.
9. 가격이 활성 Range 상단을 종가 기준으로 돌파하면 박스가 상방 돌파 상태로 변경됩니다.
10. 가격이 활성 Range 하단을 종가 기준으로 이탈하면 박스가 하방 이탈 상태로 변경됩니다.
11. Fakeout 감지를 켜면 돌파 후 다시 Range 안으로 복귀하는 경우 박스가 Fakeout 상태로 변경될 수 있습니다.
12. 중앙선은 감지된 Range 구조의 중심 위치를 시각적으로 확인하는 데 도움을 줍니다.
13. 선택형 라벨을 켤 수 있지만, 기본 설계는 박스 색상 상태를 중심으로 차트를 깔끔하게 유지하는 방식입니다.
이 구조는 복잡한 마커 없이 압축, Range 행동, 돌파 컨텍스트, 실패 돌파를 분석하는 데 도움을 줍니다.
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입력값 및 설정
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사용자는 다음 항목을 조정할 수 있습니다.
• 최소 Range 길이
• Range 폭 배수
• ATR 길이
• 기준 가격
• 중심선 모드: SMA 또는 Adaptive
• Adaptive ATR 길이
• Adaptive factor
• 겹치는 Range 병합 여부
• 돌파 후 cooldown
• 최대 활성 Range 유지 기간
• ADX 기반 Trend Pause 분류
• 돌파 버퍼
• 돌파 조건의 몸통 확인 여부
• Fakeout 감지
• Fakeout 확인 기간
• 중앙선 표시 여부
• 상단·하단 Range 라인 표시 여부
• 선택형 돌파 라벨
• 선택형 Fakeout 라벨
• Range 박스 색상
• 돌파 박스 색상
• Fakeout 박스 색상
• 테두리 투명도
• 배경 투명도
• 테두리 두께
• 신호 상태 테두리 두께
기본 설정은 차트를 깔끔하게 유지하면서 Range 구조를 가격 차트 위에서 직접 읽을 수 있도록 설계되어 있습니다.
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시각 요소
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이 스크립트는 다음 시각 요소를 포함합니다.
• Range box
• Midpoint line
• 선택 가능한 Range top / bottom lines
• Border color state
• Background color state
• 선택 가능한 break labels
• 선택 가능한 fakeout labels
Range box는 이 지표의 핵심 시각 요소입니다.
Midpoint line은 감지된 구조의 중심 레벨을 보여줍니다.
테두리와 배경색은 큰 라벨 없이도 현재 Range 상태를 구분할 수 있게 합니다.
선택형 라벨은 명시적인 텍스트 확인을 원하는 사용자를 위해 제공되지만, 기본 설계는 박스 색상 상태를 중심으로 합니다.
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참고 상태
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Unbroken Range:
가격이 감지된 변동성 기반 Range 안에 머무르는 상태입니다. 박스는 기본 Range 색상으로 유지됩니다.
Upward Break:
가격이 활성 Range 상단을 종가 기준으로 돌파한 상태입니다. 박스는 상방 돌파 색상으로 변경됩니다.
Downward Break:
가격이 활성 Range 하단을 종가 기준으로 이탈한 상태입니다. 박스는 하방 이탈 색상으로 변경됩니다.
Fakeout:
Fakeout 감지가 켜져 있을 때, 가격이 Range를 돌파한 뒤 설정된 기간 안에 다시 Range 안으로 복귀한 상태입니다. 박스는 Fakeout 색상으로 변경됩니다.
Trend Pause:
ADX 기반 분류가 켜져 있을 때, 일부 Range 구조는 순수 횡보가 아니라 강한 방향성 흐름 중의 일시적 휴식 구간으로 분류될 수 있습니다.
Adaptive Range:
Adaptive mode를 선택하면 중심선이 매 봉마다 계속 흔들리지 않고, 가격이 이전 중심선에서 충분히 멀어졌을 때만 갱신됩니다. 일부 시장 조건에서는 더 안정적인 Range 기준을 제공할 수 있습니다.
이 상태들은 정보 제공용이며, 매매 지시로 해석해서는 안 됩니다.
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사용 방법
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이 스크립트는 차트 기반 Range 구조 분석 도구로 사용하는 것이 적절합니다.
일반적인 해석 예시는 다음과 같습니다.
• 기본 Range 박스는 가격이 통제된 횡보 또는 압축 구조 안에서 움직이는 구간을 확인하는 데 사용할 수 있습니다.
• 초록색 상방 돌파 박스는 가격이 감지된 Range 상단을 벗어난 구간을 복기하는 데 사용할 수 있습니다.
• 빨간색 하방 이탈 박스는 가격이 감지된 Range 하단을 벗어난 구간을 복기하는 데 사용할 수 있습니다.
• 노란색 Fakeout 박스는 Fakeout 감지를 켰을 때 실패한 Range 돌파를 검토하는 데 사용할 수 있습니다.
• 중앙선은 Range 중심 위치를 확인하는 시각 기준으로 사용할 수 있습니다.
• Adaptive Center 모드는 더 느리게 움직이는 중심 기준을 테스트하고 싶을 때 사용할 수 있습니다.
• SMA Center 모드는 더 표준적인 Range 감지 방식을 원할 때 사용할 수 있습니다.
• 선택형 라벨은 명시적 돌파 텍스트를 원할 때 켤 수 있지만, 박스 색상 상태가 기본 시각 가이드로 설계되어 있습니다.
이 스크립트는 가격 행동, 거래량, 변동성, 지지와 저항, 추세 구조, 상위 시간대 컨텍스트와 함께 검토하는 것이 좋습니다.
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확인봉 및 리페인트 안내
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이 스크립트는 최근 종가와 ATR 기반 경계를 사용해 Range 구조를 감지합니다.
Range 박스는 새로운 캔들이 나타남에 따라 갱신될 수 있습니다.
실시간 캔들에서는 가격, ATR, Range 조건이 봉 마감 전까지 변할 수 있으므로 값이 변경될 수 있습니다.
돌파 상태는 가격이 활성 Range 경계를 벗어나는지를 기준으로 판단합니다.
보다 보수적인 분석을 원한다면 Range 돌파는 봉 마감 이후 확인하는 것이 적절합니다.
이 스크립트는 미래 가격 데이터를 사용해 시장 방향을 예측하지 않습니다.
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한계
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이 스크립트는 미래 가격 움직임을 예측하지 않습니다.
진입 또는 청산 추천을 제공하지 않습니다.
Range 돌파가 추세 지속을 보장하지 않습니다.
Fakeout 상태가 추세 반전을 보장하지 않습니다.
ATR 길이, Range 길이, 폭 배수는 Range가 표시되는 빈도에 큰 영향을 줄 수 있습니다.
저유동성 시장, 큰 갭, 뉴스 기반 급변동, 극단적 변동성 구간에서는 Range 기반 분석의 효율이 낮아질 수 있습니다.
강한 추세장에서는 일부 Range가 순수 횡보가 아니라 일시적 휴식 구간일 수 있습니다.
이 스크립트를 단독 매매 시스템으로 사용해서는 안 됩니다.
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중요 고지
────────────────────
본 게시물은 교육 및 정보 제공 목적의 차트 분석 자료입니다.
투자 자문, 특정 금융상품 거래 권유, 또는 수익 보장을 의미하지 않습니다.
모든 투자 판단과 그 결과에 대한 책임은 이용자 본인에게 있습니다. Indicateur
BTC 3 Sessions Range Analyzer [88BB]BTC 3 Sessions Range Analyzer is an intraday session range analysis tool designed for BTC traders who want to study how price behaves during the Asia, London, and US trading sessions.
The indicator tracks each session’s high, low, total range, candle body movement, average range, median range, and percentile-based volatility levels. It is built to help traders understand session behavior, compare historical volatility, and prepare more structured intraday trading plans.
This tool does not generate buy or sell signals.
It is a session statistics and range analysis tool.
Key Features
1. Three Major Trading Sessions
The indicator tracks:
Asia Session
London Session
US Session
Each session can be enabled or disabled individually from the settings panel.
2. Fully Selectable Timezone
The timezone is no longer limited to UTC+8.
Users can select from common global timezones and UTC offsets, including:
UTC-12 to UTC+14
Asia / Singapore
Asia / Kuala Lumpur
Asia / Shanghai
Asia / Taipei
Asia / Tokyo
Europe / London
Europe / Berlin
America / New York
America / Chicago
America / Los Angeles
Australia / Sydney
A custom timezone option is also available for users who want to manually enter a TradingView-supported timezone.
Default timezone: UTC+8
3. Session Range Boxes
The indicator can draw visual session boxes on the chart to show the high and low of each session.
This helps traders quickly identify:
Session high
Session low
Session range
Price expansion
Low-volatility sessions
High-volatility sessions
Breakout or compression behavior after a session ends
4. Current Session High / Low Lines
During an active session, the indicator can display the live session high and low.
This allows traders to observe whether BTC is still building range, expanding beyond the session high, or sweeping below the session low.
5. Historical Range Statistics
For each session, the dashboard calculates:
Current range
Average range
Median range
70% range level
85% range level
Average body size
Suggested TP reference zone
Suggested SL reference zone
These values are based on the selected historical lookback sessions.
6. TP / SL Reference Zones
The TP and SL values shown in the dashboard are statistical reference ranges based on historical session median range.
They are not entry signals and should not be used alone.
They are designed only to help traders estimate whether a target or stop distance is reasonable compared with historical BTC session volatility.
7. English / Chinese Language Support
The dashboard supports:
English
Chinese
Users can switch the display language directly from the settings.
8. No Repainting Design
This indicator does not use request.security() and does not rely on future data.
Completed session statistics are only calculated after the session ends.
How This Indicator Can Be Used
This tool can help traders answer questions such as:
How wide is the current Asia / London / US session range?
Is today’s BTC session range small, normal, active, or unusually volatile?
Is the current session already larger than its historical median?
Is BTC expanding after a compressed session?
Is the market too quiet for active trading?
Is the expected TP / SL distance reasonable compared with session volatility?
Which session usually gives better volatility for the selected BTC market?
Recommended Usage
This indicator is best used on lower intraday timeframes such as:
3-minute
5-minute
15-minute
Recommended market:
BTC perpetual futures
BTC spot markets
Other highly liquid BTC pairs
For best results, use normal candlestick charts.
Important Notes
This indicator is a volatility and session range study tool.
It does not predict price direction.
It does not provide financial advice.
It does not guarantee trading results.
It does not tell users when to buy or sell.
All trading decisions should be made with proper risk management, market structure analysis, liquidity context, position sizing, and personal trading rules.
Disclaimer
This script is provided for educational and analytical purposes only.
Trading involves risk.
Past session behavior does not guarantee future results.
Users are responsible for their own trading decisions.
Tags / Keywords
BTC, Bitcoin, Session Range, Asia Session, London Session, US Session, Intraday Range, Volatility, Range Analyzer, Timezone, 88BB, Session Statistics, Trading Session, Market Range, Crypto Trading Tool Indicateur
Indicateur
Smart Range ProjectionSmart Range Projection — Daily High/Low Forecast from Opening Volatility
OVERVIEW
This indicator projects the likely shape of the trading day early in the session, anchoring everything to the day's opening price. It plots the expected daily range envelope, an expansion range for potential trend day extension, and reversal zones near the projected extremes where
price often exhausts or turns.
The projection is built from a blend of four independent volatility inputs: daily ATR, opening volatility, CPR width, and an optional VIX multiplier. Once the opening window completes, the levels lock in for the rest of the session and do not shift.
HOW IT WORKS
1. Daily ATR Baseline
The previous day's confirmed ATR sets the expected full-day travel.
A user-defined multiplier (default 1.0x) converts this into the projected day range.
2. Opening Volatility Factor
The indicator measures the high-low range of the first N bars after the session opens (default 3 bars) and compares it to a rolling 20-day average of opening ranges. An unusually wide opening stretches the projection. An unusually narrow opening tightens it. The influence is
user-controlled (default 0.5).
3. CPR Width Lean
Central Pivot Range width is calculated from the previous day's high, low, and close. The current day's CPR width is compared to its 20-day average. A narrow CPR (relative to history) widens the projection because narrow CPRs statistically precede trending or expansion days.
A wide CPR tightens the projection.
4. VIX Multiplier (Optional)
An optional volatility-index input scales the entire projection based on the regime. Above the user-defined neutral level, the range widens.
Below it, the range tightens. Disabled by default. Enable only if your local volatility index is available on TradingView.
5. Reversal and Expansion Zones
- Projected High and Projected Low: the expected daily range envelope
- Expansion High and Low: dashed lines beyond the normal range, marking trend day extension targets
- Reversal Zones: shaded bands just inside the projected extremes where price often exhausts on normal days
- Expansion Zones: shaded bands between the normal envelope and expansion lines, highlighting trend day extension territory
NON-REPAINTING DESIGN
- Prior-day values use historical offset with lookahead_off
- Day open is tracked locally via session change detection
- Projection levels lock once the opening window completes and remain fixed for the rest of the session
- No future data access, no lookahead leak
INPUTS
- Daily ATR length and base range multiplier
- Expansion multiplier and reversal zone percentage
- Opening window bars and volatility influence
- Optional VIX symbol, neutral level, and toggle
- CPR lean toggle, dashboard toggle, level rounding toggle
- Color customization for all elements
DASHBOARD
A status panel shows projected high and low, expansion high and low, day lean classification (Trend or Range bias from CPR width), measured opening volatility, and the active VIX multiplier.
ALERTS
Four alert conditions are available:
- Price reached projected day high
- Price reached projected day low
- Price hit expansion high (trend day extension)
- Price hit expansion low (trend day extension)
HOW TO USE
The projected high and low serve as the day's expected range boundaries.
Price reaching these zones early often coincides with exhaustion on range days. The expansion lines act as continuation targets when strong directional moves break the normal range envelope.
The day lean classification in the dashboard helps set expectations.
A Trend lean (narrow CPR) suggests price is more likely to reach the expansion lines. A Range lean (wide CPR) suggests price is more likely to oscillate within the normal envelope and reverse at the extremes.
This indicator works on intraday timeframes where multiple bars fit within a session. It is most effective on actively traded instruments with reliable opening sessions.
NOTES
This is a technical analysis tool intended for educational and informational purposes. Volatility projections are statistical estimates based on historical patterns and do not guarantee price will reach the projected levels. Always apply proper risk management and combine with
your own trading methodology.
CREDITS
Original implementation. Uses TradingView built-in ATR, security, and array functions combined with original opening volatility and CPR width lean methodology. Indicateur
Skew MTF Trend + Regime (fork)Skew MTF Trend + Regime, a fork of "Skew MTF Trend" by Skew (@52kskew), used with credit. All original trend logic is his; this version adds one column.
What's added: a "Regime" dot next to each timeframe's direction arrow, describing the character of the move right now:
- green = ORDERLY (clean move)
- amber = CHOPPY (volatility expanding)
- red = WHIPSAW (volatility spiking, MA read noisy)
How: per timeframe, ratio of short- to long-window realized volatility: stdev(log returns, 5) / stdev(log returns, 30). Above 1.4 = amber, above 2.0 = red.
What it is / isn't: it describes how the trend is behaving, not where price goes next. It is not a buy/sell signal, and it has no predictive edge (tested on BTC daily, it does not call tops or bottoms). Treat it as situational awareness: orderly vs choppy.
Note: the table reflects the developing higher-timeframe bar, so the current cell updates until that bar closes (same behavior as the underlying trend arrows).
Original: Indicateur
Stratégie
Donchian Quantile Channel [forexobroker]Donchian Quantile Channel replaces the classic Donchian min/max envelope with robust order-statistics. The upper rail is the 90th-percentile high, the lower rail is the 10th-percentile low, and the middle spine is the 50th-percentile close, all measured over the same lookback. Channel width is then ranked against its own 200-bar history to mark expansion versus compression. Breakouts only fire when the channel is in the expansion half of its own history, which screens out quiet-channel pokes that classic Donchian treats the same as real range breaks.
🔶 ALGORITHM
1. A lookback N (default 50) defines the quantile window.
2. Upper rail = percentile_nearest_rank(high, N, 90); spine = percentile_nearest_rank(close, N, 50); lower rail = percentile_nearest_rank(low, N, 10). Using percentile_nearest_rank ignores single extreme prints that would otherwise pin a min/max envelope.
3. Width = upper - lower, ranked over the width-rank lookback (default 200 bars) using percentrank.
4. The expansion gate compares the current width rank to the Min Width Rank input (default 50). Above the threshold means the channel is wider than half its own history.
5. Crossovers of close against the upper or lower rail are detected with crossover/crossunder.
6. Signals only fire when a rail is broken inside the expansion regime, position state is flat or opposite, cooldown is satisfied and barstate.isconfirmed is true.
🔶 SIGNAL LOGIC
- Buy: close crosses above the upper quantile AND width rank is above the minimum AND session filter passes AND not already long AND cooldown bars elapsed AND barstate.isconfirmed.
- Sell: close crosses below the lower quantile AND width rank is above the minimum AND session filter passes AND not already short AND cooldown bars elapsed AND barstate.isconfirmed.
A single posState flag prevents same-side re-entry until the opposite signal resets it.
🔶 INPUTS
- Channel group: quantile lookback N default 50, upper percentile default 90, middle default 50, lower default 10, width-rank lookback default 200.
- Signal Logic group: min width rank percent (default 50) for the expansion gate, cooldown bars default 15.
- Filters group: session restriction toggle off by default with a 0000-2400 default window.
- Visual group: gradient fill, dashboard, 3-layer glow toggles plus full color overrides and dashboard background.
🔶 ALERTS
DQC Buy, DQC Sell, DQC Any Signal, DQC Upper Break, DQC Lower Break, DQC Spine Cross Up, DQC Spine Cross Dn, DQC Expansion, DQC Compression, DQC Extreme Width, DQC Extreme Squeeze, DQC Webhook JSON.
🔶 LIMITATIONS
- Percentile rails are step-like; on short lookbacks they move only when a window slot rolls off, so the channel can sit flat for several bars even as price moves.
- The expansion gate hides breakouts in quiet markets; on instruments that habitually trend on low realised range the filter will skip valid trades.
- Cooldown is a fixed bar count; it does not adapt to timeframe shifts.
- Percentiles are non-anticipatory but the channel itself only stabilises once N bars of history exist; early history shows wider, less reliable rails.
- The instrument target is ES; on illiquid symbols the upper/lower rails can be pinned to the same single print across multiple bars.
Indicateur
Dempster-Shafer Evidence Fusion [forexobroker]Dempster-Shafer Evidence Fusion combines six independent child evidences (EMA slope, RSI deviation, ATR-normalized return, signed volume z-score, range-expansion conviction, close-in-range positioning) into a single mass distribution over the hypothesis frame {Long, Short, Hold} using Dempster's rule of combination. Unlike a weighted-average composite where conflicting child signals dilute the score, Dempster-Shafer explicitly tracks epistemic uncertainty as a separate Hold mass and resolves conflict via a conflict denominator, so the combined output is properly normalized and the Hold mass quantifies disagreement among children. The unique angle is principled belief fusion rather than ad hoc voting or averaging.
🔶 ALGORITHM
1. Six child evidences are computed each bar. Each child produces a signed strength in (-1, 1).
2. Strength is mapped to a mass triplet: m(Long) = max(s,0) * |s|, m(Short) = -min(s,0) * |s|, m(Hold) = 1 - |s|. Sums equal one.
3. Children: (1) ATR-normalized EMA slope, tanh-squashed; (2) (RSI - 50)/50; (3) tanh of (close - close )/atr; (4) signed volume z-score, tanh-squashed; (5) range-expansion ratio signed by return direction, tanh-squashed; (6) (close - lowest(low,N))/(highest(high,N) - lowest(low,N)) re-centered to (-1, 1).
4. Pair-wise Dempster fusion: for two evidences (m1, m2), conflict K = m1(L)m2(S) + m1(S)m2(L); m12(L) = (m1(L)m2(L) + m1(L)m2(H) + m1(H)m2(L)) / (1-K). Symmetric for Short. Hold collects m1(H)m2(H)/(1-K). After fusion the triplet is renormalized for floating-point safety.
5. All six evidences are cascaded pair-by-pair to a final triplet (m_L, m_S, m_H).
6. Conviction equals max(m_L, m_S, m_H). The threshold (default 0.55) defines when one hypothesis dominates.
7. A signal fires when the dominant mass exceeds the threshold and standard gates pass.
🔶 SIGNAL LOGIC
- Buy: combined m(Long) above the signal threshold AND session filter passes AND position is not already long AND cooldown bars elapsed AND barstate.isconfirmed.
- Sell: combined m(Short) above the signal threshold AND session filter passes AND position is not already short AND cooldown bars elapsed AND barstate.isconfirmed.
Because m(L) + m(S) + m(H) = 1 by construction, both buy and sell cannot trigger on the same bar; ties resolve as Hold.
🔶 INPUTS
- Calculation group: EMA Length (default 21), EMA Lookback (default 5), RSI Length (default 14), ATR Length (default 14), Volume StDev Len (default 20), Range Avg Length (default 20), Position-In-Range Len (default 20).
- Signal Logic group: Combined Mass Threshold (default 0.55), cooldown bars (default 15).
- Filters group: optional session restriction (default 0000-2400).
- Visual group: dashboard toggle, 3-layer glow toggle, long/short/hold colors and dashboard background.
🔶 ALERTS
DSE Buy, DSE Sell, DSE Any Signal, DSE Long Cross, DSE Short Cross, DSE Uncertain, DSE High Conviction, DSE Net Long, DSE Net Short, DSE Webhook JSON.
🔶 LIMITATIONS
- Dempster's rule is sensitive to high-conflict situations; when child signals disagree strongly the denominator (1-K) becomes small and a near-zero numerator can amplify noise. The script floors the denominator at 1e-10.
- Six children all derived from the same OHLCV stream are not strictly independent evidences; the assumption underlying classical Dempster-Shafer is somewhat relaxed here.
- The tanh squashing of slope, return, and volume scales is opinionated; instruments with very different volatility profiles may need different child mapping ranges.
- A high conviction Hold mass means children disagree; this is information, not a problem to fix, but it does mean stretches of low signal density are expected.
- Volume is used as an evidence input; on symbols without exchange volume that child collapses to near-zero strength and the remaining five carry the consensus.
Indicateur
Zach's Quantum Harmonic OscillatorThe Quantum Harmonic Oscillator script models market momentum by applying the mechanical principles of a physical spring to asset data.
Financial assets frequently exhibit mean-reverting behavior, acting as if they are tethered to an average price line. Standard indicators track this distance linearly, which fails to capture the accelerating risk of a snapback as prices stretch further away from the mean.
This engine implements Hooke's Law to model market tension accurately:
A. The Spring Constant : Simulates market inertia and asset-specific liquidity constraints.
B. Exponential Tension : Squaring the normalized displacement ensures that minor price fluctuations generate negligible energy scores, while rapid, extended vertical moves generate exponentially higher potential energy numbers.
C. The Snapback Effect : By tracking the accumulation of this energy, the tool identifies the precise structural limits where market momentum exhausts itself, providing a mathematical framework to predict a rapid return to the baseline equilibrium.
The engine replaces arbitrary guessing with structured, institutional-grade logic. By applying a nonlinear potential energy model U = 0.5 * k * x**2, it isolates deep structural exhaustion from normal market noise. Built-in volatility scaling, strict US session time-locking, and lookahead-free multi-timeframe filtering ensure that the data remains highly reliable and entirely optimized for real-time execution.
Strategy Architecture
This strategy is highly functional and mathematically sound due to four distinct engineering choices in the Pine Script code:
1. True Mathematical Mean Reversion (The Taylor Series Principle)
In physical sciences, almost any system near a stable equilibrium naturally behaves like a harmonic oscillator because its potential energy can be approximated as a parabola. In trading, standard mean-reversion tools (like Bollinger Bands) only track linear distance from an average.
- By squaring the price displacement (Δx)², the script mimics true physical tension. Small deviations generate negligible energy, while large deviations generate exponentially higher energy. This accurately isolates true structural exhaustion from routine market fluctuations.
2. Strict Volatility Normalization
Raw price distance is a misleading metric because a $5 move on a quiet day means something completely different than a $5 move during a major news event.
- The script divides the price displacement by standard deviation. This normalizes the system, ensuring that your extreme thresholds scale dynamically across different asset classes, market cycles, and high- or low-volatility regimes without requiring manual recalibration.
3. Zero-Lookahead Multi-Timeframe Data
- The code strictly specifies barmerge.lookahead_off. This ensures historical simulation data perfectly matches real-time execution, preventing the script from "looking into the future" and rendering back test results completely reliable.
4. The Liquidity Control Filter
Executing mean-reversion strategies during illiquid market phases (such as pre-market, after-hours, or major holidays) often leads to massive slippage and false breakouts.
- The in_session filter restricts trade entries exclusively to regular US equity trading hours (09:30 AM to 04:00 PM EST). This aligns the strategy with peak daily volume and options market liquidity, filtering out erratic overnight price action.
Strategy Report & Results Analysis
The "Unit-Based" Testing Framework
When reviewing the Strategy Tester report, note that this system evaluates mathematical edge rather than an arbitrary starting balance. The back test is configured to trade exactly 1 fixed unit per signal (default_qty_value=1).
- Why standard account balance metrics don't apply: Evaluating a compounding cash balance creates distortion based on when you started the back test. By focusing purely on raw unit extraction, we can analyze the pure statistical edge of the harmonic oscillator without masking performance behind capital allocation size.
- How to interpret the data: Look directly at the Win Rate, Profit Factor, and Average Trade Net Profit in points or ticks. These core metrics demonstrate the system's structural advantage across changing market conditions.
Performance Summary
- High Win-to-Loss Efficiency: By ignoring minor market noise and only firing entries when potential energy reaches absolute mathematical limits, the strategy reduces overtrading and maximizes high-probability entries.
- Controlled Drawdown Profile: Because the oscillator standardizes raw price displacement against real-time volatility, it prevents catastrophic entries during extreme, un-normalized parabolic runs.
- Overnight Risk Management: While positions are permitted to hold overnight, restricting entry and exit operations strictly to liquid market windows prevents the strategy from suffering heavy slippage or execution gaps during low-volume extended hours. Stratégie
Indicateur
Indicateur
Liquidity Sweeps [Quantum Algo]Liquidity Sweeps is an open-source liquidity sweep indicator that maps resting
liquidity at swing highs and swing lows, then flags the exact moment that liquidity is swept and
rejected — the classic stop-hunt behaviour traders watch for in Smart Money Concepts (SMC).
WHAT IS A LIQUIDITY SWEEP?
A liquidity sweep (also called a liquidity grab or stop hunt) happens when price briefly spikes
beyond an obvious swing high or swing low — where stop-loss and breakout orders rest — and then
closes back inside the prior range. The wick takes the liquidity; the close shows the breakout
failed. Liquidity sitting above swing highs is buy-side liquidity (BSL); liquidity sitting below
swing lows is sell-side liquidity (SSL).
A bearish liquidity sweep occurs when buy-side liquidity above a swing high is swept and price
closes back below it. A bullish liquidity sweep occurs when sell-side liquidity below a swing low
is swept and price closes back above it.
HOW THE INDICATOR WORKS
- It detects confirmed swing highs and swing lows using a configurable pivot strength, and draws a
liquidity level at each one. Buy-side levels sit above price; sell-side levels sit below.
- Each level extends to the right until it is interacted with.
- When a candle wicks through a level but closes back inside, the indicator marks a liquidity
sweep with a label and an optional highlight on the sweeping wick.
- An optional volume filter confirms only sweeps where the sweeping candle trades above its
average volume, filtering out low-conviction wicks.
- If price instead closes fully through a level, that is treated as a clean break (a plain
liquidity grab / breakout), not a sweep, and the level is retired without a signal.
WHAT IT SHOWS
- Mapped buy-side (BSL) and sell-side (SSL) liquidity levels.
- Bullish and bearish liquidity sweep markers, the moment a level is swept and rejected.
- Optional wick highlighting on the sweep candle.
- A dashboard showing bullish/bearish sweep counts, the last sweep direction, and the nearest
un-swept buy-side and sell-side levels with their percentage distance from price.
HOW TO USE IT
Liquidity sweeps are most useful as a timing and context tool, not a standalone buy/sell system.
A common workflow:
- Mark the obvious highs and lows where liquidity is likely resting.
- Wait for a sweep into one of those pools (a wick through, close back inside), ideally with the
volume filter confirming participation.
- Look for confirmation in your own process — a market-structure shift, an order block, a
fair-value-gap fill, or higher-timeframe trend alignment — before acting.
- A bearish sweep above resistance can precede a move down; a bullish sweep below support can
precede a move up. Always define risk beyond the swept extreme.
SETTINGS
- Pivot Strength: how many bars define a swing; higher values keep only major liquidity pools.
- Max Levels per Side: how many recent levels to keep mapped.
- Volume Confirmation: toggle, average length, and multiplier to qualify a sweep.
- Treat Clean Breaks as Grabs: retire levels that are broken through rather than swept.
- Line width, style, and transparency for clear level visibility.
- Full colour controls and a movable dashboard.
ALERTS
Three named alert conditions are included: Bullish Liquidity Sweep, Bearish Liquidity Sweep, and
Any Liquidity Sweep.
DISCLAIMER
For educational purposes only. This is a technical analysis tool, not financial advice, and it does
not predict price. Trading involves risk and you can lose your capital. No indicator is profitable
on its own — always do your own research and use proper risk management. Indicateur
Realized Volatility Regime Indicator [v1]Realised Volatility Regime Indicator
The Realised Volatility Regime Indicator is designed to help traders understand the current volatility environment of a market.
This is not a buy or sell signal indicator. It is a volatility regime filter that helps traders decide whether the market is in a low, normal, high, or extreme volatility state.
The indicator is useful for identifying whether conditions are better suited to breakout preparation, normal trading, momentum continuation, volatility shock management, or post-shock cooling.
It can be used across FX, crypto, indices, commodities, futures, and liquid stocks.
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WHAT THE INDICATOR MEASURES
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The indicator calculates realized volatility from recent price changes using log returns.
It then annualizes that volatility and compares the current reading to its own historical range using percentile ranking.
This allows the indicator to classify volatility relative to the asset’s own recent behaviour.
For example, EUR/USD and Bitcoin naturally have different volatility profiles. Instead of comparing raw volatility values, this indicator asks:
“Is current volatility high or low relative to this market’s own recent history?”
That makes the tool more adaptive across different asset classes and timeframes.
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MAIN COMPONENTS
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1. Realised Volatility
Realised volatility measures how much the price has actually moved over a selected lookback period.
Higher realised volatility means the price has been moving more aggressively.
Lower realised volatility means the price has been more compressed.
2. Annualised Realised Volatility
The indicator converts per-bar volatility into an annualised volatility value using the Bars Per Year input.
Suggested Bars Per Year settings:
• Daily FX / indices: 252
• Daily crypto: 365
• 1-hour FX: approximately 6240
• 1-hour crypto: approximately 8760
The annualised volatility value is shown in the dashboard.
3. Volatility Percentile
The volatility percentile is the main plotted line.
It shows where current realised volatility ranks compared to recent historical volatility.
General interpretation:
• 0–25%: Low volatility
• 25–75%: Normal volatility
• 75–90%: High volatility
• Above 90%: Extreme volatility
The percentile method is more adaptive than using fixed volatility levels.
4. Volatility Direction
The indicator also shows whether volatility is:
• Expanding
• Contracting
• Flat
This matters because high volatility with expansion is different from high volatility with contraction.
For example:
• High volatility + expanding = momentum conditions may be active
• High volatility + contracting = cooling or exhaustion may be developing
• Low volatility + contracting = compression may be building
5. Market State
The dashboard classifies the market into one of the following states:
• Compression
• Expansion
• Vol Shock
• Cooling
• Neutral
These states are designed to provide a quick summary of the current volatility environment.
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VOLATILITY REGIMES
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Low Vol
Low Vol means volatility is compressed relative to recent history.
This can suggest:
• Quiet market conditions
• Narrower price ranges
• Lower realized movement
• Breakout risk may be building
Low volatility does not predict direction. It only tells the trader that the market is compressed.
Common use cases:
• Prepare for breakout setups
• Monitor range boundaries
• Avoid forcing trades inside tight ranges
• Wait for volatility expansion confirmation
Normal Vol
Normal Vol means volatility is within its average historical range.
This is usually the most balanced environment.
Common use cases:
• Standard position sizing
• Normal stop placement
• Trend or range trading depending on price structure
• Standard technical confirmation
High Vol
High Vol means volatility is elevated relative to recent history.
This can indicate:
• Stronger directional movement
• Wider ranges
• Higher uncertainty
• Greater stop-loss risk
• Better momentum conditions
Common use cases:
• Reduce position size
• Use wider stops
• Avoid tight entries
• Look for continuation if volatility is still expanding
• Avoid fading strong moves too early
Extreme Vol
Extreme Vol means volatility is in the upper range of its recent history.
This often appears around:
• Central bank decisions
• CPI / inflation data
• NFP or labour market data
• Earnings shocks
• Geopolitical events
• Crypto liquidation cascades
• Flash crashes
• Major breakouts or breakdowns
Common use cases:
• Reduce exposure
• Avoid excessive leverage
• Avoid chasing large candles
• Wait for structure to stabilize
• Watch for cooling before considering mean reversion
Extreme volatility is not automatically a reversal signal. Markets can remain extreme for longer than expected.
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MARKET STATE DEFINITIONS
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Compression
Compression occurs when volatility is low and still falling.
This may indicate that the market is coiling before a larger move, but it does not predict direction.
Use compression to prepare, not to predict.
Expansion
Expansion occurs when volatility is high and rising.
This may support breakout or momentum conditions.
In expansion regimes, traders should be careful about fading strong directional moves too early.
Vol Shock
Vol Shock occurs when volatility is extreme and still rising.
This is a high-risk environment.
It may reflect:
• News repricing
• Panic movement
• Liquidation pressure
• Stop cascades
• Forced positioning adjustment
• Macro repricing
During Vol Shock conditions, risk control is more important than signal chasing.
Cooling
Cooling occurs when volatility is still elevated but has started to contract.
This may suggest the initial shock or momentum burst is slowing.
Cooling is not a reversal signal by itself. It simply means volatility pressure is easing.
Better reversal confirmation may require:
• Failed continuation
• Break of short-term structure
• Return inside a prior range
• Reclaim of a key moving average
• Re-entry after an extreme move
Neutral
Neutral means there is no strong volatility condition.
In this state, traders should rely more heavily on price structure, trend, support/resistance, and normal trade rules.
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HOW TO READ THE INDICATOR
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The main line is the volatility percentile.
Colour guide:
• Green = Low Vol
• Blue = Normal Vol
• Orange = High Vol
• Red = Extreme Vol
The dashboard shows:
• Vol Regime
• Annualized Realized Volatility
• Volatility Percentile
• Vol Direction
• Regime Score
• Market State
Regime Score:
• 1 = Low Vol
• 2 = Normal Vol
• 3 = High Vol
• 4 = Extreme Vol
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HOW TO USE THE INDICATOR
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Use this indicator as a regime filter.
The main purpose is to help decide what type of trading approach is better suited to current market conditions.
Suggested interpretation:
• Low Vol + Compression: prepare for breakout, but wait for direction
• Normal Vol: use standard technical trading rules
• High Vol + Expansion: momentum continuation may be more likely
• Extreme Vol + Vol Shock: reduce size and avoid chasing
• High / Extreme Vol + Cooling: monitor for exhaustion or mean-reversion confirmation
The indicator should not be used as a standalone signal. Volatility tells you about the trading environment, not direction.
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PRACTICAL TRADING WORKFLOW
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1. Identify the current volatility regime.
Check whether the market is in Low Vol, Normal Vol, High Vol, or Extreme Vol.
2. Check volatility direction.
Is volatility expanding, contracting, or flat?
3. Match the strategy to the regime.
Low volatility may favour breakout preparation.
High volatility may favour momentum continuation.
Extreme volatility may require defensive risk management.
Cooling may support watching for failed continuation or exhaustion.
4. Adjust risk.
As volatility rises, position size should generally fall.
High volatility regimes often require wider stops and smaller size.
5. Use price structure for entries.
Do not enter trades based only on volatility.
Use support/resistance, trend, market structure, liquidity zones, or other confirmation.
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SUGGESTED SETTINGS
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FX 1-Hour
• Realized Volatility Lookback: 30 to 50
• Bars Per Year: 6240
• Volatility Percentile Lookback: 252
• Smooth Volatility: True
• Smoothing Length: 5
Daily FX / Indices
• Realized Volatility Lookback: 20 to 30
• Bars Per Year: 252
• Volatility Percentile Lookback: 252
• Smooth Volatility: True
• Smoothing Length: 3 to 5
Crypto 1-Hour
• Realized Volatility Lookback: 50
• Bars Per Year: 8760
• Volatility Percentile Lookback: 500
• Smooth Volatility: True
• Smoothing Length: 5 to 10
Daily Crypto
• Realized Volatility Lookback: 20 to 30
• Bars Per Year: 365
• Volatility Percentile Lookback: 365
• Smooth Volatility: True
• Smoothing Length: 3 to 5
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HOW TO COMBINE WITH EXPECTED MOVE BANDS
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This indicator pairs well with an expected-move projection indicator.
The Realized Volatility Regime Indicator tells you what volatility environment the market is in.
Expected Move Bands tell you where price may reasonably move over a selected horizon.
Suggested combined framework:
• Low Vol / Compression: expected move bands may be narrow; breakout risk may be building
• Normal Vol: use 1σ and 2σ expected move levels normally
• High Vol / Expansion: momentum continuation may be more likely
• Extreme Vol / Shock: reduce size and avoid chasing into extreme levels
• High or Extreme Vol Cooling: watch for re-entry, exhaustion, or failed continuation
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EXAMPLES
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Example 1: Low Volatility Compression
If the dashboard shows:
• Vol Regime: Low Vol
• Vol Direction: Contracting
• Market State: Compression
This means the market is quiet and compressed.
A trader may prepare breakout alerts above resistance and below support, but should wait for price confirmation.
Example 2: High Volatility Expansion
If the dashboard shows:
• Vol Regime: High Vol
• Vol Direction: Expanding
• Market State: Expansion
This means volatility is rising and momentum conditions may be active.
A trader may favour continuation setups, avoid tight stops, and avoid fading strong moves too early.
Example 3: Extreme Volatility Shock
If the dashboard shows:
• Vol Regime: Extreme Vol
• Vol Direction: Expanding
• Market State: Vol Shock
This means the market is in a stress condition.
A trader may reduce exposure, avoid over-leverage, and wait for stabilization before entering new trades.
Example 4: Extreme Volatility Cooling
If the dashboard shows:
• Vol Regime: Extreme Vol
• Vol Direction: Contracting
• Market State: Cooling
This means volatility remains elevated, but the shock is starting to fade.
A trader may monitor for failed continuation or mean-reversion confirmation, but should not assume an automatic reversal.
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RISK MANAGEMENT NOTES
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This indicator is especially useful for risk adjustment.
Possible applications:
• Reduce size during High Vol and Extreme Vol regimes
• Avoid tight stops when volatility is expanding
• Avoid over-targeting trades when volatility is compressed
• Use wider stops only if position size is reduced
• Avoid fading extreme moves without confirmation
• Use compression regimes to prepare, not predict
• Use cooling regimes to monitor possible exhaustion
A practical rule:
As volatility rises, position size should generally fall.
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WHAT THIS INDICATOR IS BEST FOR
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This indicator is best used for:
• Volatility regime detection
• Market environment filtering
• Risk management
• Breakout preparation
• Momentum confirmation
• Volatility shock detection
• Strategy selection
• Trade sizing context
It is most useful when combined with price action, market structure, support/resistance, trend filters, and macro or event awareness.
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WHAT THIS INDICATOR IS NOT
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This indicator is not:
• A standalone trading strategy
• A buy/sell signal generator
• A prediction model
• A guarantee of future volatility
• A replacement for risk management
• A complete trading system
Volatility describes the market environment. It does not tell you direction by itself.
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IMPORTANT LIMITATIONS
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The indicator uses historical realized volatility. It does not know future volatility.
Volatility can change rapidly after:
• Economic data releases
• Central bank decisions
• Earnings reports
• Geopolitical events
• Liquidity shocks
• Crypto liquidation cascades
• Market open or close effects
The indicator does not include:
• Options implied volatility
• Order flow
• Market depth
• Positioning data
• Fundamental data
• News sentiment
• Liquidity conditions
Use it as a decision-support tool, not as a standalone trading system.
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FINAL NOTES
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The Realized Volatility Regime Indicator helps traders think in terms of volatility, risk, and regime.
Instead of asking only whether price is bullish or bearish, this tool helps answer:
• Is the market quiet or active?
• Is volatility rising or falling?
• Is the market compressed or expanding?
• Is the current move part of a volatility shock?
• Should I use normal size, reduce size, or wait?
• Is this environment better for breakout, momentum, range, or defensive trading?
The indicator is designed to improve trade context and risk discipline.
Indicateur
ForgeQuant AI | Regime + LSTM + R:R [MarketFragments]ForgeQuant AI
A regime-aware overlay that combines four systems into a single read on the
chart: a regime classifier, a deep recurrent LSTM-style memory cell, a 0-100
confluence edge score, and a dynamic ATR-based risk/reward engine.
Important up front: this is a research preview. It has NOT been forward tested,
and no performance claims are made. See the notes at the bottom.
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HOW IT WORKS
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STEP 1 -- REGIME DETECTION
Volatility percentile (ATR rank) and a directional-movement trend-strength
reading classify each bar into one of six regimes: Strong Trend Bull, Strong
Trend Bear, High-Vol Chop, Mean Reversion, Breakout Potential, or Neutral. The
chart background shades to match.
STEP 2 -- DEEP LSTM MEMORY CELL
A 2-layer recurrent memory cell processes an engineered input vector built from
normalized volume, momentum vs the 21 EMA, volatility-of-volatility, and RSI
deviation. Layer 1 runs a fast cell and a slow cell; Layer 2 is a stacked
context cell. Gate weights adapt online via a clipped, momentum-smoothed
pseudo-BPTT update, with optional attention-weighted readout and layer-norm
input scaling. The cell outputs a hidden state, a confidence reading, a regime
bias (via an adaptive bias band), and an anomaly flag when price behavior
diverges sharply from the learned state.
This is a heuristic recurrent filter written in Pine -- not a trained neural
network. Treat it as an adaptive smoother, not a forecast.
STEP 3 -- CONFLUENCE EDGE SCORE
A 0-100 score blends five inputs: market structure (fair-value gaps and volume
absorption), volume behavior, momentum (RSI and the 9 EMA), higher-timeframe
trend (60-minute), and the LSTM bias/anomaly state.
STEP 4 -- DYNAMIC RISK & REWARD
Suggested risk % scales by regime (reduced in chop, trimmed further on an
anomaly). Stop and target are ATR multiples, with the target stretched by LSTM
confidence. A forward-projected R:R cloud draws the target (green) and stop
(red) zones from the latest close.
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SIGNALS
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Long Edge score >= 62, RSI > 52, a bullish FVG or absorption bar, and no
active LSTM anomaly.
Short Edge score >= 62, RSI < 48, a bearish FVG or absorption bar, and no
active LSTM anomaly.
Triggers evaluate on confirmed bars only.
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WHAT YOU SEE
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Background shade Current regime
Cyan line LSTM hidden state plotted around price (× ATR amplitude)
Green/Red cloud Dynamic R:R -- target (green) and stop (red)
Triangles Long (L, up) and Short (S, down) signals
Dashboard panel Regime, edge score, LSTM confidence, suggested risk %,
dynamic R:R, anomaly status, attention split, bias band
Gate plots Optional forget/input/output gate activations (debug)
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SETTINGS
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Display Regime background, panel position/size, diagnostics, gates
LSTM Memory Cell Enable, memory speed, anomaly sensitivity, attention,
layer-norm, hidden-state plot amplitude
Regime-Bias Band Auto (stdev-scaled) vs manual, sensitivity, lookback,
floor/ceiling
Dynamic Risk Base risk %, ATR stop/target multiples, chop multiplier,
R:R cloud toggle and forward extend
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IMPORTANT NOTES
─────────────────────────────────────────────────────────────
-- This indicator has NOT been backtested or forward tested
-- No performance claims are made
-- Shared as a research tool for community review
-- Risk, stop, and target values are illustrative sizing suggestions, not
trade instructions
-- Results will vary by instrument, timeframe, and market conditions
-- This is not financial advice
-- Trading involves substantial risk of loss
-- Past results do not guarantee future performance
-- Use for educational and research purposes only
─────────────────────────────────────────────────────────────
Free for public use Indicateur
BB Squeeze BreakoutBB Squeeze Breakout
Precision Breakout is a volatility compression and breakout indicator based on Bollinger Bands, Keltner Channels, momentum filters, volume confirmation, and ATR-based risk levels.
The goal of this tool is to help traders read when price is compressing, when volatility starts expanding again, and whether a breakout has enough confirmation to be considered stronger or weaker.
This indicator is not a trading system by itself. It is made to support chart reading and should be used together with market structure, support and resistance, liquidity zones, session context, and personal risk management.
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MAIN IDEA
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Markets often move through two phases:
1. Compression
Price contracts, Bollinger Bands become tighter, and the market prepares for a possible expansion.
2. Expansion
Price breaks outside the bands, volatility increases, and a directional move can start.
This script tracks those phases with:
- Bollinger Bands
- Keltner Channels
- Squeeze detection
- Bollinger Bandwidth
- %B position
- Candle quality
- RSI momentum
- Volume expansion
- OBV confirmation
- MFI confirmation
- A/D confirmation
- ADX trend strength
- MACD confirmation
- EMA trend filter
- ATR-based SL and TP levels
- A dashboard for quick reading
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HOW THE SIGNALS WORK
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A bullish breakout appears when price closes above the upper Bollinger Band for the required number of confirmation bars.
A bearish breakout appears when price closes below the lower Bollinger Band for the required number of confirmation bars.
The script then checks additional conditions such as candle body quality, momentum, volume, OBV slope, MACD behavior, ATR expansion, Bollinger Bandwidth expansion, and post-squeeze context.
The final signal depends on the confluence score and the selected filters.
A strong signal means that the breakout structure is present and the required confirmations are aligned.
A weak signal means that price broke outside the Bollinger Band, but the score or one of the active filters was not strong enough.
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MINI TUTORIAL FOR BEGINNERS
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1. Add the indicator to the chart.
2. Start with the default settings.
3. Look for a squeeze phase, where Bollinger Bands compress inside the Keltner Channel.
4. Wait for a squeeze release or a confirmed breakout outside the Bollinger Bands.
5. Check the dashboard:
- Squeeze: shows if compression is active.
- Post-SQ: shows if the market recently left a squeeze.
- BandWidth: shows if volatility is low or expanding.
- %B: shows where price is inside or outside the bands.
- SNIPER: shows the current confluence score.
- Signal: shows BUY, SELL, WEAK BUY, WEAK SELL, or WAIT.
6. If a signal appears, check if it agrees with the trend, support/resistance, and market structure.
7. Use the ATR-based Entry, SL, TP1, TP2, and TP3 levels as visual planning references.
8. Do not take a signal blindly. Always check the context before making a decision.
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EXAMPLE CASES
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Example 1: Bullish post-squeeze breakout
Price has been moving sideways, the Bollinger Bands are tight, and the squeeze is active. Then price closes above the upper Bollinger Band with a strong candle, rising volume, improving RSI, and expanding bandwidth. The dashboard shows a bullish score above the minimum threshold. A BUY label can appear, and the ATR risk levels show Entry, SL, TP1, TP2, and TP3.
Example 2: Bearish breakdown
Price loses support and closes below the lower Bollinger Band. RSI moves below 50, OBV weakens, MACD confirms downside pressure, and the candle closes near the low of its range. If the score and active filters agree, a SELL label can appear.
Example 3: Weak breakout
Price closes outside the Bollinger Band, but the candle is small, volume is not expanding, or momentum is weak. In this case, the script can show a WEAK signal instead of a confirmed one. This means the structure exists, but confirmation is not strong enough.
Example 4: Head fake
Price briefly breaks outside a band, then moves back inside the Bollinger structure. The script can mark this as a possible head fake. This helps identify failed breakouts, especially in choppy or low-volume markets.
Example 5: Band walk
During strong trends, price can continue moving along the upper or lower Bollinger Band. The script marks these band walk conditions to show possible trend continuation behavior.
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INPUTS EXPLAINED
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BOLLINGER BANDS
BB Length
Controls the moving average period used for the Bollinger Band basis. The default value is 20, which is the classic Bollinger setting.
BB StdDev
Controls the standard deviation multiplier used to build the upper and lower bands. The default value is 2.0, which is the common standard setting.
Neon Glow
Adds a visual glow effect around the Bollinger Bands.
Heat Zone
Colors the area between the Bollinger Bands depending on price position inside the band range.
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KELTNER / SQUEEZE
Keltner Length
Controls the length used for the Keltner Channel calculation.
Keltner Mult
Controls the ATR multiplier used to build the Keltner Channel.
Show Keltner
Shows or hides the Keltner Channel on the chart.
Post-Squeeze Window
Defines how many bars after a squeeze release are still considered part of the post-squeeze phase.
Squeeze Ready Lookback
Looks back over a selected number of bars to detect when Bollinger Bandwidth is near a low-compression zone.
Show Squeeze Dots
Shows dots during squeeze conditions and squeeze release events.
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BREAKOUT SIGNALS
Confirmation Bars
Defines how many consecutive closes outside the Bollinger Band are required before confirming a breakout.
Show BUY/SELL Labels
Shows or hides the main BUY and SELL labels.
Show Arrows
Shows or hides the arrow markers on the chart.
Show Tiny Info Labels
Shows or hides smaller labels such as weak signals and head fake warnings.
Head Fake Lookback
Controls how many bars are checked to detect a failed breakout after price moved outside a band.
Band Walk Bars
Controls how many bars are required to detect a band walk condition.
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SNIPER ENGINE
Min Confluence Score
Sets the minimum score required for a confirmed signal. A higher value gives fewer signals but requires stronger confirmation.
Min Body/Range Ratio
Defines how large the candle body must be compared to the full candle range. This helps filter weak candles and dojis.
Close Must Be In Top/Bot %
For bullish candles, the close should be near the top of the range. For bearish candles, the close should be near the bottom of the range.
ATR Expansion Factor
Checks if current ATR is expanding compared to its average. This helps confirm volatility expansion.
Require Momentum Acceleration
Uses momentum behavior, mainly RSI acceleration, as part of the confirmation logic.
Require Volume Expansion
Uses volume expansion as part of the breakout quality reading.
Require BB Width Expansion
Checks if Bollinger Bandwidth is expanding during the breakout.
Anti-Wick Rejection Filter
Helps reject breakouts when the previous candle shows a strong wick against the breakout direction.
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FILTERS
Use RSI Filter
Activates or disables RSI confirmation.
RSI Length
Controls the RSI calculation period.
Use OBV Filter
Activates or disables OBV confirmation.
Use Volume Spike Filter
Activates or disables volume spike confirmation.
Volume MA Length
Controls the moving average length used to compare current volume.
Volume Min x MA
Defines how much current volume must exceed the volume average.
Use MFI Filter
Activates or disables Money Flow Index confirmation.
MFI Length
Controls the MFI calculation period.
Use A/D Filter
Activates or disables Accumulation/Distribution confirmation.
Use ADX Filter
Activates or disables ADX trend strength confirmation.
ADX Length
Controls the ADX calculation period.
ADX Min
Defines the minimum ADX value required when the ADX filter is active.
Use MACD Filter
Activates or disables MACD confirmation.
Use EMA Trend Filter
Activates or disables EMA trend confirmation.
EMA Fast
Controls the fast EMA length.
EMA Slow
Controls the slow EMA length.
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RISK MANAGEMENT
Show SL / TP
Shows or hides Entry, Stop Loss, and Take Profit levels.
Show SL/TP Zones
Shows or hides the colored risk and target zones.
Show SL/TP Labels
Shows or hides the Entry, SL, TP1, TP2, and TP3 labels.
SL ATR x
Controls the ATR multiplier used to calculate the Stop Loss distance.
TP1 ATR x
Controls the ATR multiplier used to calculate the first Take Profit level.
TP2 ATR x
Controls the ATR multiplier used to calculate the second Take Profit level.
TP3 ATR x
Controls the ATR multiplier used to calculate the third Take Profit level.
Enable TP3
Shows or hides the third Take Profit level.
RM Label Offset Bars
Moves the risk management labels slightly to the right of the current price area. The labels and zones update automatically as new candles appear.
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DASHBOARD
Show Dashboard
Shows or hides the dashboard panel.
Position
Moves the dashboard to the selected chart corner.
High Contrast Panel
Makes the dashboard easier to read with stronger background contrast.
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VISUAL ELEMENTS
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The indicator can display:
- Bollinger Bands
- Bollinger glow effect
- Heat zone between bands
- Keltner Channels
- Squeeze dots
- Squeeze release dots
- BUY and SELL labels
- Weak breakout labels
- Head fake labels
- Band walk markers
- ATR-based Entry, SL, TP1, TP2, TP3 levels
- Colored risk and target zones
- A dashboard with market state information
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IMPORTANT NOTES
────────────────────────────
This script is an indicator, not a strategy.
It does not place trades.
It does not guarantee profitable results.
It does not predict the future.
Signals can fail in ranging, low-liquidity, high-spread, or news-driven market conditions.
Users should test the indicator on their own symbols, timeframes, and trading style before using it in live market decisions.
Risk management remains the responsibility of the user. Indicateur
ORB + Fib Breakout Signals (Strategy)ORB + Fib Breakout Signals (Strategy)
An opening-range breakout (ORB) strategy combined with Fibonacci levels and a
defined risk model. It marks the session's opening range, goes long on a break
above the range high and short below the range low, then manages the trade with
an ATR-based stop, an R-multiple target, and an optional breakeven move.
How it works
- Opening range — builds the high/low of the first 15/30/60 minutes of your
chosen session (timezone configurable).
- Entry — long on a close (or wick) above the ORB high, short below the ORB low;
one signal per direction per day by default.
- Fib levels — plots the standard retracements (.236–.786) inside the range plus
the 1.272 / 1.618 extensions as reference targets.
- Risk model — stop by ATR (default), Fib 0.5, opposite side of the range, or
fixed ticks; target as a multiple of risk (default 2R); optional move to
breakeven after 1R.
- Optional filters — a higher-timeframe EMA trend filter and a scale-out that
books half at 1R and lets the remainder run.
- Daily guards — max entries per day, daily loss limit, optional daily profit
lock, and flat-at-session-close, for prop-style risk rules.
Inputs are grouped (Opening Range, Signals, Fibonacci, Trend Filter, Risk Model,
Daily Guards) so you can adapt it to any index future or timeframe.
Notes
- Commission and slippage are included in the defaults — set them in Properties
to match your broker before drawing conclusions.
- Performance varies with symbol, timeframe, and settings. Test on your own data
and forward-test on a simulator before trading it live.
- This is an educational tool, not financial advice. Past backtest results do
not guarantee future performance. Stratégie
Stock & Market Health ChecklistMarket Health Checklist
A compact, fully-configurable dashboard that reads market and single-stock trend health at a glance. Instead of stacking a dozen moving averages on your chart, it collapses the whole picture into a clean colour-coded table — green for healthy, red for weak, neutral grey for raw readings.
It's built around two independent sections:
■ MARKET — calculated from a fixed Signal Ticker (default QQQ) regardless of what chart you're on. This is your top-down regime read: is the broad tape healthy right now?
■ STOCK — calculated from whatever symbol you're currently viewing. Click through your watchlist and every line updates to the stock in front of you.
What it tracks
MARKET section:
Up to 4 MA crossover signals (e.g. 5/10, 10/20) — green when fast > slow
Up to 4 MA slope signals — green when the MA is rising
Price vs MA checks
VIX vs threshold — green below (calm), red above (fear)
T2108 / breadth (default symbol MMFI) — red overbought, green washed-out
RSI with overbought/oversold colouring
STOCK section:
Price above 10/20/50/200 MA
Slope (up/down) of each of those MAs
RSI of the current stock
Current daily $ Volume, auto-formatted (e.g. $1.24B / $45.30M)
ATR in dollars (default 3× daily ATR) — handy for stop and target sizing
Customisation
Every moving-average row has its own EMA or SMA selector and its own length
Each signal can be toggled on or off independently
Pin VIX, T2108 and the STOCK stats to Daily values so they read identically on any chart and any timeframe (recommended)
Full appearance control: table position (9 anchors), text size, vertical or horizontal layout, section headers on/off, live values on/off, and individual colours for green / red / neutral / text / headers / border
Notes
For VIX, use TVC:VIX — it resolves real-time via request.security on most plans, whereas CBOE:VIX requires the paid CBOE Global Indices add-on.
Referenced symbols (VIX, T2108) use the latest available daily value, so the dashboard stays consistent whether the market is open or closed.
This is a decision-support tool, not a signal generator or financial advice. It summarises conditions you'd otherwise eyeball manually — how you act on them is up to you. Indicateur
Corwin-Schultz Spread Bands [forexobroker]Corwin-Schultz Spread Bands estimates the effective bid-ask spread directly from daily high-low data using the Corwin-Schultz (2012) two-bar estimator, then turns the rolling spread into a stress regime and a pair of price bands. The unique angle is using a peer-reviewed microstructure spread formula intended for daily data on any timeframe to flag liquidity stress on the chart and time entries when stress fades into a directional trend.
🔶 ALGORITHM
1. For each pair of adjacent bars compute beta = (ln(H_t / L_t))^2 + (ln(H_{t-1} / L_{t-1}))^2 and gamma = (ln(max(H_t, H_{t-1}) / min(L_t, L_{t-1})))^2.
2. Compute alpha = (sqrt(2 x beta) - sqrt(beta)) / (3 - 2 x sqrt(2)) - sqrt(gamma / (3 - 2 x sqrt(2))).
3. Raw spread = 2 x (exp(alpha) - 1) / (1 + exp(alpha)). Clamp to the range.
4. Smooth with EMA (default 5) to produce a stable percentage spread.
5. Rolling regime stats: 100-bar (default) median and stdev of the smoothed spread; threshold = median + k x stdev (default k = 1.0).
6. In-stress = smoothed spread above threshold. Exiting stress = was above on the prior bar and below now.
7. Trend filter: close versus 20-SMA (default).
8. Visual bands: close +/- (spread / 2) x close x mult.
🔶 SIGNAL LOGIC
- Buy: spread regime just exited stress AND close > trend SMA AND session filter passes AND posState was not long AND cooldown elapsed AND barstate.isconfirmed.
- Sell: spread regime just exited stress AND close < trend SMA AND session filter passes AND posState was not short AND cooldown elapsed AND barstate.isconfirmed.
A flip-prevention posState plus cooldown bars (default 15) avoid stacking signals inside a single regime transition.
🔶 INPUTS
- Spread Estimator: smoothing EMA default 5, regime lookback default 100, stdev multiplier default 1.0.
- Signal Logic: trend SMA length default 20, cooldown bars default 15.
- Filters: optional session window default 0000-2400.
- Visual: spread band multiplier default 1.0, glow, fill, bands, stress bgcolor, neon palette, dashboard.
🔶 ALERTS
CSS Buy, CSS Sell, CSS Any Signal, CSS Enter Stress, CSS Exit Stress, CSS Spread Rising, CSS Spread Falling, CSS Trend Up, CSS Trend Down, CSS Extreme Spread, CSS Webhook JSON.
🔶 LIMITATIONS
- The estimator was designed for daily bars; on very low timeframes the high-low range gets dominated by tick noise and the spread value is noisier than the daily case.
- Spread is computed in price-fraction terms; reporting in basis points assumes that interpretation is meaningful for the instrument.
- The regime threshold depends on a 100-bar lookback, so on fresh history the threshold is unstable until the buffer is full.
- Signals require the regime to flip, so during long sideways regimes with no stress event the indicator can sit idle for many bars.
- The 20-SMA trend filter is intentionally simple and will misclassify direction during tight ranges.
Indicateur
Copula Tail Dependency [forexobroker]Copula Tail Dependency estimates the empirical lower- and upper-tail dependence between price returns and volume changes using a rank-based copula. Rather than measuring linear correlation (which collapses to a single number and ignores tail behavior), the indicator measures whether extreme co-occurrences are abnormally frequent. The unique angle is that crossovers of the upper- or lower-tail measure above a threshold mark genuine joint-extreme regimes where return-volume co-movement is strong, while ordinary days leave both measures low.
🔶 ALGORITHM
1. Each bar's one-step log return and volume change are computed.
2. Both series are rank-transformed within the last N (default 50) bars; the rank divided by N produces a uniform marginal U for returns and V for volume changes.
3. The empirical lower-tail dependence is lambda_L = count(U <= u AND V <= u) / count(V <= u) for u equal to the tail fraction (default 0.1).
4. The empirical upper-tail dependence is lambda_U = count(U >= 1-u AND V >= 1-u) / count(V >= 1-u).
5. Both quantities live on ; values near 0 indicate independence at the tails, values near 1 indicate strong joint-extreme behavior.
6. A signal threshold (default 0.5) defines the line above which the tail measure is treated as a co-movement regime.
7. Bullish signal: lambda_U crosses above the threshold. Bearish signal: lambda_L crosses above the threshold.
🔶 SIGNAL LOGIC
- Buy: lambda_U crosses above the threshold AND session filter passes AND position is not already long AND cooldown bars elapsed AND barstate.isconfirmed.
- Sell: lambda_L crosses above the threshold AND session filter passes AND position is not already short AND cooldown bars elapsed AND barstate.isconfirmed.
The cross-up trigger filters out sustained-tail regimes that have already been priced in; entries fire only when joint-tail strength is freshly established.
🔶 INPUTS
- Calculation group: Window N (default 50), Tail Fraction u (default 0.1), Signal Threshold (default 0.5).
- Signal Logic group: cooldown bars (default 15).
- Filters group: optional session restriction (default 0000-2400).
- Visual group: dashboard toggle, 3-layer glow toggle, upper-tail and lower-tail colors, dashboard background.
🔶 ALERTS
CTD Buy, CTD Sell, CTD Any Signal, CTD Upper Tail Up, CTD Lower Tail Up, CTD Upper Tail Dn, CTD Lower Tail Dn, CTD Symmetric Tails, CTD Webhook JSON.
🔶 LIMITATIONS
- Volume is required, so on symbols without exchange volume the lower/upper tail estimates degrade to noise.
- The rank transform uses a fixed look-back, so the marginal CDF is local rather than global; very long-trend regimes can suppress tail measures.
- With N = 50 and u = 0.1, the upper and lower tails each contain only 5 reference points; small sample noise is expected.
- The indicator measures co-movement direction, not magnitude; it does not size the move.
- A high lambda_U can persist during slow grinding uptrends and then mean-revert, so re-entries from cool to hot are the cleanest signals.
Indicateur
