Hide Out ProHide Out Pro —
Hide Out Pro is built for intraday option traders who analyze CALL (CE) and PUT (PE) charts separately to identify the stronger side of the market. It filters sideways phases, detects premium-decay zones, and highlights structured breakout and pullback entries using forward-projected volatility levels.
1. Hide Out Trend Filter (Sideways Market Protection)
Options lose value quickly during sideways movement.
The Hide Out engine uses volatility expansion to determine when the market is active or stagnant.
Pink-masked candles → weak momentum / premium-decay zone → avoid entries
Breakout from the mask → real trend activation
Works independently on CALL and PUT charts
This keeps option buyers out of choppy, time-decay conditions.
2. Day Opening Range (DOR)
The script marks the first 3 minutes of the session (designed for Indian market timing) and locks the High, Low, and Range for the rest of the day.
Directional Bias Using CALL & PUT Charts
CALL above DOR Low → bullish continuation potential
PUT above DOR Low → bearish continuation potential
Price below DOR Low → premium-decay zone.
Both inside DOR → sideways / low-quality movement
This helps traders identify which option side is gaining strength.
3. Leading Lines (Projected 6 Minutes Ahead)
Volatility Price Lines (Entry System)
Forward-projected volatility lines guide high-probability entries:
Green line → momentum structure
Amber line → liquidity pullback structure
After a Hide Out breakout, pullbacks into these lines provide controlled, rule-based entries for CE/PE buyers.
Target Line (Exit & Risk Control)
A thin forward-projected blue line marking short-term volatility expansion:
Avoid entering above this line
Use it for profit-booking or trailing stop-loss
This prevents late entries into overstretched premium zones.
4. Base Price Labels (Entry + Stop-Loss)
After trend confirmation, the script waits for a pullback into the Volatility Price Lines.
A Base Price label appears only when conditions align and includes:
Entry price
Stop-loss level (volatility-based)
This provides structured, predefined-risk entries.
5. Hide Out Label (Trend Confirmation)
A Hide Out label appears when price breaks out of the masked zone, signaling the start of true momentum and avoiding premature entries.
Works independently on CALL and PUT charts.
6. LP Divergence Label (Momentum Exhaustion Warning)
The script uses a proprietary calculation to generate an internally calculated low-participation metric.
When price forms a higher high but participation weakens, an LP label warns of:
Premium exhaustion
Trend slowdown
Reversal probability
Useful for avoiding late entries or tightening stops.
7. Best Timeframe
Optimized for the 3-minute timeframe, though it works on all timeframes.
How to Use (Quick Workflow)
Apply Hide Out Pro separately on CALL and PUT charts.
Identify which chart stays above its DOR Low → potential strength side.
Wait for a Hide Out breakout → confirms trend.
Enter on pullbacks to the Volatility Price Lines.
Avoid entries above the Target Line.
Use Target Line for exits or trail SL.
Watch LP labels for exhaustion or profit-booking signals.
Why the Script Is Closed-Source
Hide Out Pro uses a custom, self-protected computational framework combining volatility modelling, forward-projected structures, and multi-layer filters designed specifically for option premiums.
This includes proprietary logic for:
Sideways-market suppression (Hide Out mask)
DOR-based premium-decay detection
Forward-projected volatility lines
Base Price pullback and SL mapping
Internally calculated low-participation divergence
Because the methodology uses original algorithms, proprietary calculations, sequencing rules, and interaction logic not available in any public indicator, the source code is protected to prevent duplication and reverse-engineering.
תנודתיות
Financial Earthquakes, LPPLSConcept Overview
Sornette (ETH Zurich) pioneered the Log-Periodic Power Law Singularity (LPPLS) model, drawing a profound analogy between financial crashes and physical ruptures/earthquakes. In this framework, speculative bubbles exhibit super-exponential price growth (power-law acceleration toward a critical time tₚ) decorated by accelerating log-periodic oscillations — signatures of herding behavior and hierarchical feedback loops among investors. These "financial earthquakes" often end in regime changes: crashes (positive bubbles) or sharp rebounds (negative bubbles). This indicator provides a practical adaptation of Sornette's core ideas, without requiring complex nonlinear fitting on rolling windows.
Components
Multi-scale Local Hurst Exponent (m): Approximates the power-law exponent in the LPPLS model.
A rough local proxy for the exponent m is computed on five different lookback periods (default: 5, 14, 30, 70, 140 bars) using the relation:
local H ≈ (log(range) − log(ATR)) / log(period)
The average of these five values serves as a dynamic estimate of the bubble's "super-exponentiality" (persistent trending behavior when H > 0.5).
Log-Periodic Oscillation Term:
C1 × t^H × (1 + C2 × cos(ω × log(t) + φ))
where t is distance from an arbitrary recent reference point. This introduces the characteristic log-periodic "ripples" that accelerate as the hypothetical critical time approaches.
DSI Hurst (0–100 oscillator):
The raw LPPLS-inspired series is dynamically scaled over a 100-bar lookback into a bounded 0–100 range (similar to a stochastic or RSI).
≈ 50 → neutral / random-walk regime
87 → extreme super-exponential + log-periodic pressure (potential positive bubble / end-of-rally critical point)
< 13 → extreme anti-persistent pressure (potential negative bubble / end-of-bear critical point)
Visual Elements
Red line: DSI Hurst oscillator (0–100)
Horizontal lines at 13, 50, 87
Bar coloring: fuchsia when DSI > 87 (bubble warning), yellow when DSI ≈ 0 (extreme tightening)
Circle shapes at the top → potential critical point (DSI extreme + Hurst consistent across scales + ongoing log-periodic ripples) — analogous to Sornette's "financial earthquake" warning
Circle shapes at the bottom → potential critical pullback / regime shift in the opposite direction
Usage
High DSI Hurst (especially > 87) with confirming circle → increasing probability of an imminent regime change (often a crash after a bubble).
Low DSI Hurst (especially < 13) with confirming circle → potential sharp rebound after a negative bubble.
The indicator works on any timeframe and asset class (stocks, indices, crypto, forex) where herding and positive-feedback dynamics can appear.
*Default values (periods) optimized for SPX.
Notes
This is an interpretation of Sornette's LPPLS theory adapted for Pine Script limitations. It does not perform full nonlinear LPPLS calibration (which requires heavy optimization and is used in academic confidence/trust indicators). It captures the spirit: multi-scale persistence + log-periodic component → early warning of critical transitions.
Combine with price action, volume, fundamentals or any other form of analysis, and risk management.
No indicator predicts crashes with certainty — it only highlights periods where the market structure resembles the pre-crisis patterns repeatedly documented in Sornette's research (1987, 2000, 2008, 2015 China, Bitcoin, etc.).
TSO Lite – Trend & Momentum Unified OscillatorTrend & momentum unified oscillator for structural price movement.
💡 Why TSO is Different
Most oscillators separate their functions:
• MACD → trend inflection
• RSI → momentum strength
• Stochastics → oscillation bias
Because they rely on averaged price data, these indicators often react slowly
or fail to reveal structural transitions in time.
TSO works differently.
It interprets structural shifts occurring inside price movement, capturing both
trend changes and momentum strength within a single unified engine.
Since it does not depend on moving averages, transitions appear earlier and clearer.
TSO Lite is the simplified edition of TSO (Triple Structure Oscillation),
designed to visualize structural rhythm and directional flow with clarity.
🔹 Included in TSO Lite:
• TSO Line – immediate directional response
• TSO Flow – structural background flow
• TSO Pulse – expansion/compression behavior
• Lightweight and clean visualization
🔹 Not Included in Lite:
• TSO Drive
• TSO Extremes
• Automation / Webhook alerts
• Multi-layer structural engine (PRO only)
TSO Lite is ideal for:
• beginners
• lightweight structural analysis
• users who want a clean and simple version of TSO
TSO Lite vs TSO PRO – Feature Comparison
───────────────────────────────────────────────
TSO LITE | TSO PRO
───────────────────────────────────────────────
Core Layers ✔ 3 layers | ✔ Full multi-layer engine
TSO Drive ✘ Not included | ✔ Dynamic response
TSO Extremes ✘ Not included | ✔ Turning-zone detection
Automation ✘ Not supported | ✔ Webhook automation
Best For Beginners | Advanced traders
───────────────────────────────────────────────
🔗 Upgrade to TSO PRO
For deeper structural detection, high-resolution mapping, and automation:
• Monthly subscription: tradesmith6.gumroad.com
• Yearly subscription (best value): tradesmith6.gumroad.com
📌 Licensing
TSO Lite is a free publicly available script.
Redistribution, resale, or reverse-engineering attempts are prohibited.
📌 Disclaimer
This tool does not guarantee profit. All trading is at your own risk.
구조적 가격 움직임을 기반으로 추세와 모멘텀을 동시에 관찰할 수 있는 통합형 오실레이터입니다.
💡 왜 TSO가 다른가?
일반적인 오실레이터는 기능이 나누어져 있습니다:
• MACD → 추세 전환 신호
• RSI → 모멘텀 강도
• Stochastics → 진동 편향
이러한 지표들은 대부분 ‘평균 기반 계산’을 사용하기 때문에
신호가 늦게 나오거나 중요한 전환 구간을 놓치는 경우가 많습니다.
TSO는 다른 방식으로 작동합니다.
가격 움직임 내부에서 발생하는 구조적 변화를 해석하여
추세 변화와 모멘텀 강도를 하나의 통합된 엔진 관점에서 읽어냅니다.
평균값에 의존하지 않기 때문에, 전환 구간이 더 빠르고 명확하게 표시됩니다.
TSO Lite는 TSO(Triple Structure Oscillation)의 간소화 버전으로,
가격 움직임의 구조적 리듬과 방향성 흐름을 깔끔하게 시각화하도록 설계되었습니다.
🔹 TSO Lite 포함 기능:
• TSO Line – 즉각적인 방향 반응
• TSO Flow – 구조적 배경 흐름
• TSO Pulse – 확장/압축 리듬 변화
• 가볍고 직관적인 레이아웃
🔹 TSO Lite 미포함 기능:
• TSO Drive
• TSO Extremes
• 자동매매(Webhook)
• 다층 구조 엔진(PRO 전용)
TSO Lite는 다음 사용자에게 적합합니다:
• 초보자
• 가벼운 구조 분석
• 심플한 형태의 TSO를 원하는 사용자
TSO Lite vs TSO PRO – 기능 비교
───────────────────────────────────────────────
TSO LITE | TSO PRO
───────────────────────────────────────────────
핵심 레이어 ✔ 3 레이어 | ✔ 멀티 레이어 엔진
TSO Drive ✘ 미포함 | ✔ 동적 반응
TSO Extremes ✘ 미포함 | ✔ 전환 구간 감지
자동매매 지원 ✘ 지원 안 함 | ✔ Webhook 자동화
적합한 사용자 초보자 | 고급 트레이더
───────────────────────────────────────────────
🔗 TSO PRO 업그레이드 안내
더 깊은 구조 분석, 고해상도 감지, 자동매매(Webhook)가 필요하다면:
• 월간 구독: tradesmith6.gumroad.com
• 연간 구독(가성비): tradesmith6.gumroad.com
📌 라이선스
TSO Lite는 무료로 제공되는 공개 스크립트입니다.
재배포, 재판매, 역설계 시도는 금지되어 있습니다.
📌 면책 조항
본 도구는 수익을 보장하지 않으며, 모든 거래 책임은 사용자 본인에게 있습니다.
LGZ – Liquidity Gravity Zones v1 📌 LGZ – Liquidity Gravity Zones (SVI + Net CVD + Volume)
Original Liquidity-Driven Price Magnet Model by Thomas Aaroon
📘 Concept Overview
LGZ (Liquidity Gravity Zones) is a new, original liquidity-based price-attraction model built using three core components:
SVI (Shock Volume Index) – measures abnormal volume spikes at each strike
Net CVD (NCP = CE_CVD − PE_CVD) – the real directional order-flow imbalance
Total Volume (CE + PE) – true liquidity density at each strike
Using these three elements, the indicator calculates Liquidity Gravity Weight (LGW) for every strike and identifies the strongest zones that attract price during the session.
🧠 Why This Indicator?
Traditional OI-based methods (long build-up, short build-up, OI change etc.) often lag.
LGZ focuses only on:
Real traded volume
Actual buy/sell aggression (CVD)
Shock events
Dealer hedging pressure
Strike-level liquidity clusters
This makes it far more responsive for intraday traders.
⭐ Core Formula
Liquidity Gravity Weight (LGW)
LGW = |SVI| × |Net CVD| × Total Volume
Where:
SVI = Shock Volume Index (Z-score based)
Net CVD (NCP) = CE_CVD − PE_CVD
Total Volume = CE_volume + PE_volume
LGW indicates how strongly a strike is pulling price toward it.
🎯 What the Indicator Shows
✔ Top Liquidity Gravity Zones (LGZ-1, LGZ-2, LGZ-3)
These are the strongest price magnets for the day.
✔ Gravity Lines on Chart
Each LGZ is plotted as a horizontal magnet line extending to the right.
✔ Strike-Level Liquidity Table
Shows:
Strike
SVI (Shock intensity)
LGW (Gravity strength)
This table gives a complete picture of the intraday liquidity landscape.
📈 How to Use (Intraday Trading Strategy)
🔵 1. Price gravitates toward LGZ-1
If price is below LGZ-1 → upward pull
If price is above LGZ-1 → downward pull
🔵 2. LGZ Flips = Trend Change
If LGZ-1 suddenly jumps to a different strike:
→ strong trend acceleration
🔵 3. LGZ Cluster = Reversal / Consolidation Zone
Multiple LGZ levels around the same strike indicate
→ liquidity saturation → reversal or slowdown.
🔵 4. Combine with Price Action
Best clarity on 5-minute timeframe
Use 1-minute only for entry.
🔬 Why LGZ Works
The indicator models the same reality driving option markets:
Where option volume + orderflow (CVD) + shock liquidity concentrate,
market makers hedge, and price moves toward that strike.
This is the foundation of dealer hedging mechanics and liquidity-based price movement.
🔧 Inputs
Symbol prefix (e.g., NIFTY)
Expiry (YYMMDD)
Center strike & range
Number of gravity zones
Color customization
920 Order Flow SATY ATR//@version=6
indicator("Order-Flow / Volume Signals (No L2)", overlay=true)
//======================
// Inputs
//======================
rvolLen = input.int(20, "Relative Volume Lookback", minval=5)
rvolMin = input.float(1.1, "Min Relative Volume (× avg)", step=0.1)
wrbLen = input.int(20, "Wide-Range Lookback", minval=5)
wrbMult = input.float(1, "Wide-Range Multiplier", step=0.1)
upperCloseQ = input.float(0.60, "Close near High (0-1)", minval=0.0, maxval=1.0)
lowerCloseQ = input.float(0.40, "Close near Low (0-1)", minval=0.0, maxval=1.0)
cdLen = input.int(25, "Rolling CumDelta Window", minval=5)
useVWAP = input.bool(true, "Use VWAP Bias Filter")
showSignals = input.bool(true, "Show Long/Short OF Triangles")
//======================
// Core helpers
//======================
rng = high - low
tr = ta.tr(true)
avgTR = ta.sma(tr, wrbLen)
wrb = rng > wrbMult * avgTR
// Relative Volume
volAvg = ta.sma(volume, rvolLen)
rvol = volAvg > 0 ? volume / volAvg : 0.0
// Close location in bar (0..1)
clo = rng > 0 ? (close - low) / rng : 0.5
// VWAP (session) + SMAs
vwap = ta.vwap(close)
sma9 = ta.sma(close, 9)
sma20 = ta.sma(close, 20)
sma200= ta.sma(close, 200)
// CumDelta proxy (uptick/downtick signed volume)
tickSign = close > close ? 1.0 : close < close ? -1.0 : 0.0
delta = volume * tickSign
cumDelta = ta.cum(delta)
rollCD = cumDelta - cumDelta
//======================
// Signal conditions
//======================
volActive = rvol >= rvolMin
effortBuy = wrb and clo >= upperCloseQ
effortSell = wrb and clo <= lowerCloseQ
cdUp = ta.crossover(rollCD, 0)
cdDown = ta.crossunder(rollCD, 0)
biasBuy = not useVWAP or close > vwap
biasSell = not useVWAP or close < vwap
longOF = barstate.isconfirmed and volActive and effortBuy and cdUp and biasBuy
shortOF = barstate.isconfirmed and volActive and effortSell and cdDown and biasSell
//======================
// Plot ONLY on price chart
//======================
// SMAs & VWAP
plot(sma9, title="9 SMA", color=color.orange, linewidth=3)
plot(sma20, title="20 SMA", color=color.white, linewidth=3)
plot(sma200, title="200 SMA", color=color.black, linewidth=3)
plot(vwap, title="VWAP", color=color.new(color.aqua, 0), linewidth=3)
// Triangles with const text (no extra pane)
plotshape(showSignals and longOF, title="LONG OF",
style=shape.triangleup, location=location.belowbar, size=size.tiny,
color=color.new(color.green, 0), text="LONG OF")
plotshape(showSignals and shortOF, title="SHORT OF",
style=shape.triangledown, location=location.abovebar, size=size.tiny,
color=color.new(color.red, 0), text="SHORT OF")
// Alerts
alertcondition(longOF, title="LONG OF confirmed", message="LONG OF confirmed")
alertcondition(shortOF, title="SHORT OF confirmed", message="SHORT OF confirmed")
//────────────────────────────
// End-of-line labels (offset to the right)
//────────────────────────────
var label label9 = na
var label label20 = na
var label label200 = na
var label labelVW = na
if barstate.islast
// delete old labels before drawing new ones
label.delete(label9)
label.delete(label20)
label.delete(label200)
label.delete(labelVW)
// how far to move the labels rightward (increase if needed)
offsetBars = input.int(3)
label9 := label.new(bar_index + offsetBars, sma9, "9 SMA", style=label.style_label_left, textcolor=color.white, color=color.new(color.orange, 0))
label20 := label.new(bar_index + offsetBars, sma20, "20 SMA", style=label.style_label_left, textcolor=color.black, color=color.new(color.white, 0))
label200 := label.new(bar_index + offsetBars, sma200, "200 SMA", style=label.style_label_left, textcolor=color.white, color=color.new(color.black, 0))
labelVW := label.new(bar_index + offsetBars, vwap, "VWAP", style=label.style_label_left, textcolor=color.black, color=color.new(color.aqua, 0))
//────────────────────────────────────────────────────────────────────
//────────────────────────────────────────────
// Overnight High/Low + HOD/LOD (no POC)
//────────────────────────────────────────────
sessionRTH = input.session("0930-1600", "RTH Session (exchange tz)")
levelWidth = input.int(2, "HL line width", minval=1, maxval=5)
labelOffsetH = input.int(10, "HL label offset (bars to right)", minval=0)
isRTH = not na(time(timeframe.period, sessionRTH))
rthOpen = isRTH and not isRTH
// --- Track Overnight High/Low during NON-RTH; freeze at RTH open
// --- Track Overnight High/Low during NON-RTH; freeze at RTH open
var float onHigh = na
var float onLow = na
var int onHighBar = na
var int onLowBar = na
var float onHighFix = na
var float onLowFix = na
var int onHighFixBar = na
var int onLowFixBar = na
if not isRTH
if na(onHigh) or high > onHigh
onHigh := high
onHighBar := bar_index
if na(onLow) or low < onLow
onLow := low
onLowBar := bar_index
if rthOpen
onHighFix := onHigh
onLowFix := onLow
onHighFixBar := onHighBar
onLowFixBar := onLowBar
onHigh := na, onLow := na
onHighBar := na, onLowBar := na
// ──────────────────────────────────────────
// Candle coloring + labels for 9/20/VWAP crosses
// ──────────────────────────────────────────
showCrossLabels = input.bool(true, "Show cross labels")
// Helpers
minAll = math.min(math.min(sma9, sma20), vwap)
maxAll = math.max(math.max(sma9, sma20), vwap)
// All three lines
goldenAll = open <= minAll and close >= maxAll
deathAll = open >= maxAll and close <= minAll
// 9/20 only (exclude cases that also crossed VWAP)
dcUpOnly = open <= math.min(sma9, sma20) and close >= math.max(sma9, sma20) and not goldenAll
dcDownOnly = open >= math.max(sma9, sma20) and close <= math.min(sma9, sma20) and not deathAll
// Candle colors (priority: all three > 9/20 only)
var color cCol = na
cCol := goldenAll ? color.yellow : deathAll ? color.black :dcUpOnly ? color.lime :dcDownOnly ? color.red : na
barcolor(cCol)
// Labels
plotshape(showCrossLabels and barstate.isconfirmed and goldenAll, title="GOLDEN CROSS",
style=shape.labelup, location=location.belowbar, text="GOLDEN CROSS",
color=color.new(color.yellow, 0), textcolor=color.black, size=size.tiny)
plotshape(showCrossLabels and barstate.isconfirmed and deathAll, title="DEATH CROSS",
style=shape.labeldown, location=location.abovebar, text="DEATH CROSS",
color=color.new(color.black, 0), textcolor=color.white, size=size.tiny)
plotshape(showCrossLabels and barstate.isconfirmed and dcUpOnly, title="DC UP",
style=shape.labelup, location=location.belowbar, text="DC UP",
color=color.new(color.lime, 0), textcolor=color.black, size=size.tiny)
plotshape(showCrossLabels and barstate.isconfirmed and dcDownOnly, title="DC DOWN",
style=shape.labeldown, location=location.abovebar, text="DC DOWN",
color=color.new(color.red, 0), textcolor=color.white, size=size.tiny)
// ──────────────────────────────────────────
// Audible + alert conditions
// ──────────────────────────────────────────
alertcondition(goldenAll, title="GOLDEN CROSS", message="GOLDEN CROSS detected")
alertcondition(deathAll, title="DEATH CROSS", message="DEATH CROSS detected")
alertcondition(dcUpOnly, title="DC UP", message="Dual Cross UP detected")
alertcondition(dcDownOnly,title="DC DOWN", message="Dual Cross DOWN detected")
Session Indicator by FlipPointThe indicator is designed to display trading sessions on a TradingView chart. It highlights the time ranges of major sessions such as Frankfurt, London, New York, and Asia, providing the ability to analyze price behavior during different periods of the trading day.
Functional settings
1. Show history
Enables or disables the display of sessions on historical parts of the chart. If disabled, only today's sessions are shown.
2. Show Frankfurt / London / New York / Asia
Each parameter is responsible for displaying the corresponding trading session. When enabled, a highlighted zone appears on the chart, representing the time boundaries of that session.
3. Show titles
Displays text labels with the name of each session.
4. Color settings
Determines the fill color of the highlighted zones for the respective sessions.
5. Label text color
Defines the color of the session title labels.
6. PDH / PDL parameters
Show PDH — displays the previous day’s high (Previous Day High).
Show PDL — displays the previous day’s low (Previous Day Low).
PDH/PDL lines color — sets the color of the lines representing these levels.
Time zone alignment
The indicator is automatically aligned with the time zone set in the TradingView chart settings. The time boundaries of the sessions adjust to the selected time zone without requiring manual adjustments. This ensures accurate session display regardless of the user’s local time.
Session Indicator by FlipPointThe indicator is designed to display trading sessions on a TradingView chart. It highlights the time ranges of major sessions such as Frankfurt, London, New York, and Asia, providing the ability to analyze price behavior during different periods of the trading day.
Functional settings
1. Show history
Enables or disables the display of sessions on historical parts of the chart. If disabled, only today's sessions are shown.
2. Show Frankfurt / London / New York / Asia
Each parameter is responsible for displaying the corresponding trading session. When enabled, a highlighted zone appears on the chart, representing the time boundaries of that session.
3. Show titles
Displays text labels with the name of each session.
4. Color settings
Determines the fill color of the highlighted zones for the respective sessions.
5. Label text color
Defines the color of the session title labels.
PDH / PDL parameters
Show PDH — displays the previous day’s high (Previous Day High).
Show PDL — displays the previous day’s low (Previous Day Low).
PDH/PDL lines color — sets the color of the lines representing these levels.
Time zone alignment
The indicator is automatically aligned with the time zone set in the TradingView chart settings. The time boundaries of the sessions adjust to the selected time zone without requiring manual adjustments. This ensures accurate session display regardless of the user’s local time.
区间顶底与超级趋势系统Overview:
This is a comprehensive trading system designed to capture both trend reversals and trend-following opportunities. This script combines three core modules: Long-term EMA Tunnels (Vegas Style), Dynamic Support/Resistance Zones (based on historical highs/lows), and the classic SuperTrend. It aims to help traders identify "buy low, sell high" opportunities in ranging markets and catch major waves during strong trends.
Core Features Explained
1. EMA Long-term Trend Tunnel
Configuration: The script includes three specific Exponential Moving Averages (EMAs): 144, 169, and 233.
Function: These lines form a long-term support and resistance band. Price action above these lines is generally considered a bullish trend, while price below indicates a bearish trend.
2. Dynamic Range Top/Bottom
Logic: Calculates the current market structure based on the highest and lowest prices over a specific lookback period (default 130 bars), combined with ATR (Average True Range).
Visualization: Automatically draws Resistance Boxes (Red zone) at the top and Support Boxes (Green zone) at the bottom.
Data Panel: Displays the current ATR volatility percentage and a count of Bullish/Bearish K-lines within the period to help gauge the balance of power between buyers and sellers.
Signals: Reversal arrows appear when price tests these extreme zones and shows signs of rejection.
3. SuperTrend Integration
Tool: A classic trend-following indicator based on ATR and median price.
Usage: Acts as a reliable market noise filter. When SuperTrend is green, it is recommended to look for long setups; when red, look for short setups.
Highlighting: The script supports background highlighting, allowing you to identify the current trend direction at a glance.
How to Use This System
Trend Following Strategy: When the EMA lines are aligned upwards and the SuperTrend shows a Buy signal (Green background), look for long entries on pullbacks to the SuperTrend support line or near the EMAs.
Range Reversal Strategy: When price hits the upper or lower limits of the "Dynamic Range" and a SuperTrend flip or arrow reversal signal occurs, consider counter-trend trades.
Stop Loss: It is recommended to place stop losses just outside the SuperTrend line or the Dynamic Range boxes.
Settings
EMA: You can toggle the visibility of the EMA lines on or off.
Dynamic Range: Customizable lookback period (Length) and extension settings to fit your timeframe.
SuperTrend: Fully adjustable ATR Period and Multiplier to adapt to different asset volatilities.
Disclaimer: This script is for educational purposes only and does not constitute financial advice.
概述：
这是一个专为捕捉趋势反转与顺势交易设计的综合交易系统。本脚本结合了三大核心模块：长期均线隧道（Vegas风格）、动态支撑阻力区间（基于历史高低点）以及经典的超级趋势（SuperTrend）。旨在帮助交易者在震荡行情中识别高抛低吸的机会，并在趋势行情中抓住主升浪。
核心功能解析
1. EMA 长期趋势隧道 (EMA Tunnel)
脚本内置了三条特定的指数移动平均线 (EMA)：144、169 和 233。
这些均线构成了长期趋势的支撑与阻力带。当价格位于这些均线之上时，通常视为多头趋势；反之则为空头趋势。
2. 动态顶底区间 (Dynamic Range Top/Bottom)
原理：基于过去一定周期（默认130根K线）内的最高价和最低价，结合 ATR（平均真实波幅）计算出当前的市场结构。
视觉化：图表中会自动绘制出顶部的阻力箱体（红色区域）和底部的支撑箱体（绿色区域）。
数据面板：箱体旁会显示当前的 ATR 波动率百分比，以及该周期内的 K 线买入/卖出计数，帮助判断多空力量对比。
信号：当价格触及这些极限区域并出现反转迹象时，会显示箭头提示。
3. 超级趋势 (SuperTrend)
经典的趋势跟踪工具，基于 ATR 和价格中位数计算。
用法：用于过滤市场噪音。当超级趋势为绿色时，建议只寻找做多机会；为红色时，建议只寻找做空机会。
高亮显示：脚本支持背景高亮，让你一目了然当前的趋势方向。
如何使用本指标进行交易
顺势交易：当 EMA 均线向上排列且 SuperTrend 显示买入信号（绿色背景）时，关注回调至 SuperTrend 支撑线或 EMA 附近的做多机会。
区间反转：当价格触及“动态顶底区间”的上沿或下沿，并且出现 SuperTrend 变色或箭头反转信号时，可考虑反向操作。
止损建议：建议将止损设置在 SuperTrend 线或动态箱体的外侧。
设置说明
你可以开启/关闭 EMA 显示。
可以自定义顶底区间的计算周期（Length）和延伸长度。
可以调整 SuperTrend 的 ATR 周期和乘数以适应不同的波动率。
Alzeerr Scalping StrategyAlzeerr Scalping Strategy
A high-precision intraday scalping strategy that combines VWAP, support/resistance levels, volume confirmation, RSI momentum shifts, and reversal candlestick patterns to identify low-risk, high-accuracy trade entries. The strategy only trades in the direction of the trend relative to VWAP, focuses on high-probability pullback entries, and uses tight stop-losses with small, consistent profit targets. Designed to maximize accuracy and minimize drawdown during high-liquidity market sessions.
VZO Enhanced価格の上昇バーと下降バーごとに出来高を分離し、それぞれをEMAで平滑化して算出した Volume Zone Oscillator（VZO）の改良版です。
デフォルトでは20期間のEMAを使用し、トレンド方向に対する出来高の偏りをパーセンテージで表示します。
オーバーボート／オーバーソールドの水準（初期値 +60 / -60）を背景色でハイライトし、短期トレードでの反転ポイントや勢いの弱まりを視覚的に捉えやすくしています。
This script is a modified version of the Volume Zone Oscillator (VZO) tailored for short–term trading.
It separates volume into positive volume (when the close is higher than the previous close) and negative volume (when the close is lower than the previous close), then applies EMA to:
* positive volume
* negative volume
* total volume
The oscillator is calculated as the percentage difference between positive and negative volume relative to total volume.
By default it uses a length of 20 (EMA Length = 20) and highlights overbought / oversold zones (initially +60 / -60) with background colors, making it easy to see:
* trend strength based on volume
* shifts in volume pressure
* potential reversals and divergences between price and volume.
Weekday Close vs Open — Last N (per weekday)# Weekday Close vs Open - Last N Occurrences
This indicator distills every weekday's historical open-to-close behavior into a compact table so you can see how "typical" the current session is before the day even closes. It runs independently of your chart timeframe by pulling daily OHLCV data under the hood, tracking the last **N** completed occurrences for each weekday, and refreshing only when a daily bar closes. On daily charts you can also shade every past bar that matches today's weekday (excluding the in-progress session) to reinforce the pattern visually while the table remains non-repainting.
## What It Shows
- **Win/Loss/Tie counts** - how many of the last `N` occurrences closed above the open (wins), below (losses), or inside the tie threshold you define as "flat".
- **Win % heatmap** - the win column is color-coded (deep green > deep red) so you immediately recognize strong or weak weekdays.
- **Advanced metrics (optional)** - average daily volume plus the average percentage excursion above/below the open (`AvgUp%`, `AvgDn%`) for that weekday.
- **Totals row** - aggregates every weekday into one row to estimate overall hit rate and average stats across the entire data set.
- **Weekday shading (optional)** - on daily charts you can tint every bar that matches today's weekday (all Mondays, all Fridays, etc.) for instant pattern recognition.
## How It Works
1. The script requests daily OHLCV data (non-repainting) regardless of the chart timeframe.
2. When a new daily bar confirms, it packs that day's data into one of seven arrays (one per weekday). Each day contributes five floats (O/H/L/C/V) so trimming and statistics stay in lockstep.
3. A helper function (`f_dayMetrics`) scans daily history to compute average volume, average excursion above/below the open, and win/loss/tie counts for the requested weekday.
4. The table populates on the last bar of the chart session, respecting your advanced/totals toggles and keeping text at `size.normal`.
## Reading the Table
- **Win/Loss/Tie columns**: raw counts taken from your chosen `N`.
- **Win %***: excludes ties from the denominator so it reflects only decisive closes.
- **AvgUp% / AvgDn%**: typical intraday extension (high vs open, open vs low) in percent.
- **Avg Vol**: arithmetic mean of daily volume for that weekday.
- **TOTAL row**: provides a global win rate plus volume/up/down averages weighted by how many samples each weekday contributed.
## Practical Uses
- Spot weekdays that historically trend higher or lower before entering a trade.
- Compare current price action against the typical intraday range (`AvgUp%` vs today's move).
- Filter mean-reversion vs breakout setups based on the most reliable weekday patterns.
- Quickly gauge whether today is behaving "in character" by referencing the highlighted row or the optional whole-chart weekday shading.
> **Tip:** Use smaller `N` values (e.g., 10-20) for adaptive, recent behavior and larger values (50+) to capture longer-term seasonality. Tighten the tie threshold if you want almost every candle to register as win/loss, or widen it to focus only on meaningful moves.
Top N Candle HighlighterTrack highest candle sizes on current timeframes. This short script:
1. Tracks the **top N largest candles** on the current chart
2. Option to use **body size** or **full candle range**
3. Highlights candles using `box.new()` (fully v6 compatible)
4. Optionally shows **rank and size labels**
5. Handles red, green, and doji candles differently with color
Liquidation Cascade Detector [QuantAlgo]🟢 Overview
The Liquidation Cascade Detector employs multi-dimensional microstructure analysis to identify forced liquidation events by synthesizing volume anomalies, price acceleration dynamics, and volatility regime shifts. Unlike conventional momentum indicators that merely track directional bias, this indicator isolates the specific market conditions where leveraged positions experience forced unwinding, creating asymmetric opportunities for mean reversion traders and market makers to take advantage of temporary liquidity imbalances.
These liquidation cascades manifest through various catalysts: overwhelming spot selling coupled with leveraged long liquidation forced unwinding creates downward spirals where organic sell pressure triggers margin calls, which generate additional selling that triggers more margin calls. Conversely, sudden large buy orders or coordinated buying can squeeze overleveraged shorts, forcing buy-to-cover orders that push price higher, triggering additional short stops in a self-reinforcing feedback loop. The indicator captures both scenarios, regardless of whether the initial catalyst is organic flow or forced liquidation.
For sophisticated traders/market makers deploying amplification strategies, this indicator serves as an early warning system for distressed order flow. By detecting the moments when cascading stop-losses and margin calls create self-reinforcing price movements, the system enables traders to: (1) identify forced participants experiencing capital pressure, (2) strategically add liquidity in the direction of panic flow to amplify displacement, (3) accumulate contra-positions during the overshoot phase, and (4) capture mean reversion profits as equilibrium pricing reasserts itself. This approach transforms destructive liquidation events into potential profit opportunities by systematically front-running and then fading coordinated forced selling/buying.
🟢 How It Works
The detection engine operates through a three-tier confirmation framework that validates liquidation events only when multiple independent market stress indicators align simultaneously:
► Tier 1: Volume Anomaly Detection
The system calculates bar-to-bar volume ratios to identify abnormal participation spikes characteristic of forced liquidations. The Volume Spike threshold filters for transactions where current volume significantly exceeds previous bar volume. When leveraged positions hit stop-losses or margin requirements, their simultaneous unwinding creates distinctive volume signatures absent during organic price discovery. This metric isolates moments when market makers face one-sided order flow from distressed participants unable to control execution timing, whether triggered by whale orders absorbing liquidity or cascading margin calls creating relentless directional pressure.
► Tier 2: Price Acceleration Measurement
By comparing current bar's absolute body size against the previous bar's movement, the algorithm quantifies momentum acceleration. The Price Acceleration threshold identifies scenarios where price velocity increases dramatically, a hallmark of cascading liquidations where each stop-loss triggers additional stops in a feedback loop. This calculation distinguishes between gradual trend development (irrelevant for amplification attacks) and explosive moves driven by forced order flow requiring immediate liquidity provision. The metric captures both panic selling scenarios where spot sellers overwhelm bid liquidity triggering long liquidations, and short squeeze dynamics where aggressive buying exhausts offer-side depth forcing short covering.
► Tier 3: Volatility Expansion Analysis
The indicator measures bar range expansion by computing the current high-low range relative to the previous bar. The Volatility Spike threshold captures regime shifts where intrabar price action becomes erratic, evidence that market depth has evaporated and order book imbalance is driving price. Combined with body-to-range analysis indicating strong directional conviction, this metric confirms that volatility expansion reflects genuine liquidation pressure rather than random noise or low-volume chop.
*Supplementary Confirmation Metrics
Beyond the three primary detection tiers, the system analyzes additional candle characteristics that distinguish genuine liquidation events from ordinary volatility:
► Candle Strength: Measures the ratio of candle body size to total bar range. High readings (above 60%) indicate strong directional conviction where price moved decisively in one direction with minimal retracement. During liquidations, distressed traders execute market orders that drive price aggressively without the normal back-and-forth of balanced trading. Strong-bodied candles with minimal wicks confirm forced participants are accepting any available price rather than attempting to minimize slippage, validating that observed volume and price acceleration stem from liquidation pressure rather than routine trading.
► Volume Climax: Identifies when current volume reaches the highest level within recent history. Climax volume events mark terminal liquidation phases where maximum panic or squeeze intensity occurs. These extreme participation spikes typically represent the final wave of forced exits as the last remaining stops are triggered or the final shorts capitulate. For mean reversion traders, volume climax signals provide optimal reversal entry timing, as they mark maximum displacement from equilibrium when all forced sellers/buyers have been exhausted.
*Directional Classification
The system categorizes cascades into two actionable classes:
1. Short Liquidation (Bullish Cascade): Upward price movement combined with cascade patterns equals forced short covering. This occurs when aggressive spot buying (often from whales placing large market orders) or coordinated buy programs exhaust available offer liquidity, spiking price upward and triggering clustered short stop-losses. Short sellers experiencing margin pressure must buy-to-close regardless of price, creating artificial demand spikes that compound the initial buying pressure. The combination of organic buying and forced covering creates explosive upward moves as each liquidated short adds buy-side pressure, triggering additional shorts in a self-reinforcing loop. Market makers can amplify this by lifting offers ahead of forced buy orders, then selling into the exhaustion at elevated levels.
2. Long Liquidation (Bearish Cascade): Downward price movement combined with cascade patterns equals forced long liquidation. This manifests when heavy spot selling (panic sellers, large institutional unwinds, or coordinated distribution) overwhelms bid-side liquidity, breaking through support levels where long stop-losses cluster. Over-leveraged longs facing margin calls must sell-to-close at any price, generating artificial supply waves that compound the initial selling pressure. The dual force of organic selling coupled with forced long liquidation creates downward spirals where each margin call triggers additional margin calls through further price deterioration. Amplification opportunities exist by hitting bids ahead of panic selling, accumulating long positions during the capitulation, and reversing as sellers exhaust.
🟢 How to Use
1. For Mean Reversion Traders
When the indicator highlights a short liquidation cascade (green background), this signals that shorts are experiencing forced buy-to-cover pressure, often initiated by whale bids or aggressive spot buying that triggered the squeeze. Mean reversion traders can interpret this as a temporary upward dislocation from fair value. As the dashboard shows declining momentum metrics and the cascade highlighting stops, this represents a potential fade opportunity. Enter short positions expecting price to revert back toward pre-cascade levels once the forced buying exhausts and the initial large buyer completes their accumulation.
When a long liquidation cascade triggers (red background), longs are undergoing forced sell-to-close liquidation, typically catalyzed by overwhelming spot selling that breached key support levels. This creates artificial downward pressure disconnected from fundamental value, as margin-driven forced selling compounds organic sell flow. Mean reversion traders wait for the cascade to complete (dashboard transitions from active liquidation status to neutral), then enter long positions anticipating snap-back toward equilibrium pricing as panic subsides and forced sellers are exhausted.
You can also monitor the dashboard's Volume Climax indicator. When it displays "YES" during an active cascade, this suggests the liquidation is reaching its terminal phase, whether driven by the final shorts being squeezed out or the last leveraged longs capitulating. Mean reversion entries become highest probability at this point, as maximum displacement from fair value has occurred. Wait for the next 1-3 bars after climax confirmation, then enter contra-trend positions with tight stops.
The Candle Strength metric also helps validate entry timing. When candle strength readings drop significantly after maintaining elevated levels during the cascade, this divergence indicates absorption is occurring. Market makers are stepping in to provide liquidity, supporting your mean reversion thesis. Strong candle bodies during the cascade followed by weaker bodies signal the forced flow is diminishing.
2. For Momentum & Trend Following Traders
When price breaks through a significant resistance level and immediately triggers a short liquidation cascade (green background), this confirms breakout validity through forced participation. Shorts positioned against the breakout are now experiencing margin pressure from the combination of breakout momentum and potential whale buying, creating self-reinforcing buying that propels price higher. Enter long positions during the cascade or immediately after, as the forced covering provides fuel for extended momentum continuation.
Conversely, when price breaks below key support and triggers a long liquidation cascade (red background), the breakdown is validated by forced selling from trapped longs. Heavy spot selling coupled with margin liquidations creates accelerated downside momentum as liquidations cascade through clustered stop-loss levels. Enter short positions as the cascade develops, riding the combined force of organic selling and forced liquidation for extended trend moves.
3. For Sophisticated Traders & Market Makers
► Amplification Attack Execution
Sophisticated operators can exploit cascades through systematic amplification positioning. When a short liquidation is detected (green highlight activating), often initiated by whale bids absorbing offer liquidity, place aggressive buy orders to front-run and amplify the forced short covering. This exacerbates upward pressure, pushing price further from equilibrium and triggering additional clustered stops. Simultaneously begin accumulating short positions at these artificially elevated levels. As dashboard metrics indicate cascade exhaustion (volume spike declining, climax signal appearing, candle strength weakening), flatten amplification longs and hold accumulated shorts into the mean reversion.
For long liquidations (red highlight), typically catalyzed by heavy spot selling overwhelming bid depth, execute the inverse strategy. Place aggressive sell orders to compound the panic selling, amplifying downward displacement and accelerating margin call triggers. Layer long entries at depressed prices during this amplification phase as forced liquidation selling creates artificial supply. When dashboard signals cascade completion (metrics normalizing, volume climax passing), exit amplification shorts and maintain long positions for the reversal trade.
► Market Making During Liquidity Crises
During detected cascades, temporarily adjust quote placement strategy. When dashboard shows all three confirmation metrics activating simultaneously with strong candle bodies, this indicates the highest probability liquidation event, whether from whale order flow or cascading margin calls. Widen spreads dramatically to capture enhanced edge during the liquidity vacuum. Alternatively, step away from quote provision entirely on your natural inventory side (stop offering during short cascades driven by aggressive buying, stop bidding during long cascades driven by overwhelming selling) to avoid adverse selection from forced flow.
Use cascade detection to inform inventory management. During short cascades initiated by large buy orders or short squeezes, reduce existing short inventory exposure while allowing the forced buying to push price higher. Rebuild short inventory only at the inflated levels created by liquidation pressure. During long cascades where spot selling compounds leveraged liquidation, reduce long inventory and use the forced selling to reaccumulate at artificially depressed prices rather than providing stabilizing liquidity too early.
► Sequential Positioning Strategy
Advanced traders can structure trades in phases: (1) Initial amplification orders placed immediately upon cascade detection to front-run forced flow, (2) Contra-position accumulation scaled in as displacement extends and dashboard readings intensify, (3) Amplification trade exit when metrics show deceleration or candle strength weakens, (4) Contra-position hold through mean reversion, targeting pre-cascade price levels. This sequential approach extracts profit from both the dislocation phase and the subsequent equilibrium restoration.
► Risk Monitoring
If cascade highlighting persists across many consecutive bars while dashboard volume readings remain extremely elevated with sustained strong candle bodies, this suggests sustained institutional deleveraging or persistent whale activity rather than simple retail liquidation. Reduce amplification position sizing significantly, as these extended events can exhibit delayed mean reversion. Professional counter-parties may be establishing dominant positions, limiting your edge.
When volatility spike metrics decline while cascade highlighting continues, professional absorption is occurring. Proceed cautiously with amplification strategies, as intelligent liquidity providers are already positioning for the reversal, potentially front-running your intended reversal trade. Similarly, if large liquidation wicks appear during cascades, this indicates partial absorption is happening, suggesting more sophisticated players are taking the opposite side of distressed flow.
52-Week High Drawdown (Events, Freq & Current)52-Week High Drawdown - Events, Freq & Current
OVERVIEW
Track and analyze drawdowns from 52-week highs with comprehensive statistics on drawdown events, frequency, and current market positioning. Perfect for risk management, historical analysis, and understanding volatility patterns.
KEY FEATURES
📊 Real-Time Drawdown Tracking
Visual area chart showing current intraday maximum drawdown from rolling high
Automatically plots depth below zero line for easy interpretation
Color-coded reference lines at -10% and -20% levels
📈 Event-Based Historical Analysis
Automatically categorizes drawdown cycles across four severity zones:
5-10% Drawdowns - Minor corrections
10-15% Drawdowns - Moderate pullbacks
15-20% Drawdowns - Significant corrections
20%+ Drawdowns - Major corrections/bear markets
⏱️ Frequency Metrics
Calculates average time between events for each category, displayed as "Every X months" to understand typical correction patterns.
🎯 Current Cycle Tracking
Real-time display of maximum drawdown depth in the current cycle, helping you gauge present market position.
📅 Smart Timeframe Adaptation
Auto-Adjust Mode: Automatically selects optimal lookback (Daily=252, Weekly=52, Monthly=12)
Manual Mode: Set custom lookback period for specialized analysis
HOW IT WORKS
The indicator identifies drawdown cycles - periods from one high to the next. When price touches a new rolling high, the previous cycle ends and is categorized by its maximum depth.
Cycle Logic:
Tracks deepest point reached since last high
When price touches/exceeds rolling high, cycle completes
Cycle categorized into appropriate drawdown zone
New cycle begins
This provides accurate event counting without double-counting fluctuations within larger drawdowns.
PRACTICAL APPLICATIONS
Risk Management
Understand typical drawdown patterns for position sizing
Set realistic stop-loss levels based on historical norms
Anticipate potential correction depths during bull markets
Market Context
Identify when current drawdowns are extreme vs. typical
Compare across different assets and timeframes
Historical perspective during volatile periods
Strategic Planning
Time entries during typical correction zones
Recognize when drawdowns exceed historical norms
Build resilience strategies based on frequency data
SETTINGS GUIDE
Auto-Adjust Lookback by Timeframe
Checked: Automatically uses appropriate period for chart timeframe
Unchecked: Uses manual lookback value
Manual Lookback Length
Default: 252 (trading days in a year)
Customize for specific analysis periods
Higher values = longer historical perspective
Table Position
Choose from Top Right, Bottom Right, Top Left, or Bottom Left based on your chart layout.
INTERPRETATION TIPS
Frequency data becomes more reliable with longer history (5+ years ideal)
"Never" frequency indicates zero events in available data range
Current Cycle Max shows 0.00% at new highs, otherwise displays deepest point
Compare frequencies across assets to understand relative volatility profiles
BEST USED FOR
Stocks, ETFs, and Indices with sufficient historical data
Long-term investing and swing trading strategies
Portfolio risk assessment and stress testing
Educational purposes - understanding market behavior
Multi-timeframe analysis (daily, weekly, monthly)
TECHNICAL NOTES
Uses ta.highest() for efficient rolling high calculation
Event detection logic prevents double-counting
Frequency calculated from actual data start time to present
All calculations update in real-time with each new bar
💡 Tip: Run this indicator on major indices like SPY or QQQ with maximum available history to build a comprehensive baseline for equity market corrections.
Created to provide institutional-grade drawdown analysis in an accessible format. Free to use and modify.
ATR Volatility AlertsOverview:
This is a dynamic alert tool based on the Average True Range (ATR), designed to help traders detect sudden price movements that exceed normal volatility levels. Whether you are trading breakouts or monitoring for abnormal spikes, this indicator visualizes these events on the chart and triggers system alerts when the price move exceeds your specified ATR multiplier.
Key Features:
Fully Customizable ATR Range:
You can adjust the ATR Length (Default: 14) and the Multiplier (Default: 1.5x).
Tip: Increase the multiplier (e.g., to 2.0 or 3.0) to catch only extreme volatility, or lower it for scalping smaller moves.
Visual Chart Signals:
Visual markers appear instantly when a bar's movement exceeds the ATR threshold.
Green Triangle: Indicates an Upward Spike.
Red Triangle: Indicates a Downward Spike.
Flexible System Alerts:
Designed to integrate seamlessly with TradingView's alert system. You can choose from three specific alert directions based on your strategy:
1.Price Spike Up: Triggers only on sharp upward moves.
2.Price Spike Down: Triggers only on sharp downward moves.
3.Bidirectional Volatility Alert: Triggers on BOTH huge pumps and dumps.
How to Set Alerts:
Click the "Create Alert" button in TradingView.
Select ATR Volatility Alerts in the "Condition" dropdown.
Choose the specific logic you need:
· Select Price Spike Up for bullish monitoring.
· Select Price Spike Down for bearish monitoring.
· Select Bidirectional Volatility Alert to watch for any volatility expansion.
RaymondTrending [Qanexra] - Advanced Volatility GaugePrice direction tells you where the market is going, but it doesn't tell you if it has the gas to get there.
RaymondTrending is a proprietary volatility instrument designed to measure the raw "energy" of the market. Unlike standard indicators that lag significantly, this tool uses a rapid-response composite algorithm to detect immediate shifts in market volatility.
What lies inside? The core engine is built on a multi-layered calculation of market range. It filters out static noise to provide a single, clean data stream representing the true "pulse" of the asset.
How to use it:
Rising Line: Volatility is expanding. The current trend (up or down) is backed by real volume and energy.
Falling Line: Volatility is collapsing. The market is entering a consolidation or "squeeze" phase.
Spikes: Sudden spikes often indicate breakout events or climatic tops/bottoms.
Access: This is a closed-source tool. Please contact Qanexra for access.
RaymondRatio [Qanexra] - Volatility with Doji Noise CancellationThe Problem with Standard Volatility: Most volatility indicators force a calculation on every single candle, regardless of quality. This means that during periods of market indecision (Dojis), your indicators are digesting "noise," leading to lag and false signals when the market finally moves.
The Solution: RaymondRatio Developed by Qanexra, the RaymondRatio is a sophisticated volatility gauge that introduces a proprietary "Doji Pause" mechanism. Instead of smoothing over noise, this indicator intelligently ignores it.
How It Works:
Volatility Engine: The core calculates the Raymond Trending value derived from a composite of short-term compare with the long-term volatility.
The Doji Pause: The indicator constantly monitors the Body-to-Range ratio of every candle. If a candle is detected as a Doji (indecision), the indicator freezes its calculation. It retains the last known "valid" volatility state.
The Ratio: The output is a ratio.
> 1.0: Volatility is expanding relative to the baseline (Active Market).
< 1.0: Volatility is compressing (Squeeze/Consolidation).
Key Features:
Smart Filtering: Background highlights in Gray indicate "Paused" zones where the market is undecided.
Clean Data: Prevents the baseline from being dragged down by low-quality price action.
Customizable Threshold: Users can define what constitutes a "Doji" (e.g., body is less than 30% of the range).
How to Trade: Use this as a filter for your existing strategy.
Green Light: When the Ratio is above 1.0 and rising, the market is in a valid expansion phase.
Red Light: When the Ratio is below 1.0 or "flatlining" during Doji Pauses, stay out of the market to avoid chop.
Two Supertrend Crossover SignalThis indicator is designed to visualize trend shifts using two Supertrend lines and a crossover-based signal system.
It also colors the area between the two Supertrend lines based on the current trend direction, making trend changes easy to identify at a glance.
How It Works
The indicator plots:
Fast Supertrend (shorter ATR length, lower factor)
Slow Supertrend (longer ATR length, higher factor)
A crossover between these two Supertrend lines indicates a possible trend shift.
Buy Signal
A BUY signal occurs when: Fast Supertrend crosses ABOVE Slow Supertrend
This suggests bullish momentum strengthening.
Sell Signal
A SELL signal occurs when: Fast Supertrend crosses BELOW Slow Supertrend
This suggests bearish momentum increasing.
Buy/Sell Signal Labels
The chart displays clear BUY (green) and SELL (red) labels at every crossover.
These signals help traders quickly pinpoint potential entries or exits.
This indicator is ideal for:
✓ Trend trading
✓ Swing trading
✓ Identifying momentum shifts
✓ Visual confirmation of market direction
✓ Combining with price action or EMA filters
You may adjust ATR length and multiplier depending on the timeframe:
For Scalping (1–5 min):
Fast ATR: 5–7
Slow ATR: 10–14
For Intraday (5–15 min):
Fast ATR: 7
Slow ATR: 10–14
For Swing Trading (1h–4h):
Fast ATR: 10
Slow ATR: 20
Important Notes
This indicator does not repaint the Supertrend values.
Signals are based on confirmed crossovers.
Use stop-loss and risk management appropriate for your strategy.
Always combine with market context (support/resistance, volume, etc.)
ROC x4 (Multi-Period Overlay) + Table📈 ROC x4 (Multi-Period Momentum Suite) + Compact Table
A clean, powerful momentum indicator that overlays four Rate-of-Change (ROC) periods inside a single pane — without needing to stack multiple separate indicators.
This script is designed for traders who use multi-timeframe momentum confirmation, trend strength validation, and early detection of rotation, compression, or expansion in price behavior.
🔍 What This Indicator Does
Plots 4 different ROC lengths in one panel
Includes a compact real-time ROC table that fits even in small panes
Tracks momentum shifts, trend acceleration, slowdowns, and regime transitions
Allows manual input for all 4 ROC lengths
Optional smoothing to reduce noise
Zero-line toggle for momentum direction clarity
Perfect for traders who want to monitor short-term, mid-term, and long-term ROC simultaneously.
Scalper Pro Pattern Recognition & Price Action📘 Scalper Pro Pattern Recognition & Price Action
Overview
Scalper Pro is a dynamic multi-layer trend recognition and price action strategy that integrates Supertrend, Smart Money Concepts (SMC), and volatility-based risk control.
It adapts to market volatility in real time to enhance entry precision and optimize risk.
⚠️ This script is for educational and research purposes only.
Past performance does not guarantee future results.
🎯 Strategy Objectives
Detect structural market shifts (BOS / CHoCH) automatically.
Identify Order Blocks (OB), Fair Value Gaps (FVG), and key liquidity zones.
Plot dynamic Take-Profit (TP) and Stop-Loss (SL) levels based on ATR.
Avoid low-volatility (sideways) conditions using ADX filtering.
Combine trend-following signals with structural confirmation.
✨ Key Features
Supertrend Entry Signals — Generates precise buy/sell markers based on price crossovers with the Supertrend line.
Order Block Detection — Automatically plots both Internal and Swing Order Blocks for smart money insights.
Fair Value Gap Visualization — Highlights inefficiency zones in bullish or bearish structures.
Market Structure Labels — Marks Break of Structure (BOS) and Change of Character (CHoCH) points for clear trend shifts.
Dynamic Risk Levels — Automatically generates TP/SL lines and price labels using ATR-based distance.
📊 Trading Rules
Long Entry:
• Price crosses above the Supertrend (ta.crossover(close, supertrend))
• ADX above sideways threshold (trend condition confirmed)
• Optional confirmation from a bullish BOS or CHoCH
Short Entry:
• Price crosses below the Supertrend (ta.crossunder(close, supertrend))
• ADX above threshold
• Optional confirmation from a bearish BOS or CHoCH
Exit (or Reverse):
• Opposite Supertrend crossover
• Price hits TP/SL lines
• Trend shift confirmed by internal BOS/CHoCH
💰 Risk Management Parameters
Stop Loss & Take Profit based on ATR × risk multiplier
ATR Length: 14 (default)
Risk %: 3% per trade
Sideways Filter: ADX < 15 → no trade zone
TP1–TP3 = Entry ± (ATR × 1~3)
⚙️ Indicator Settings
Supertrend Module:
ATR Length: 10
Factor: nsensitivity × 7
ADX Module:
ADX Length: 15
Sideways Threshold: 15
EMA Set:
EMA (5, 9, 13, 34, 50) × Volatility Factor (3)
SMA Filter:
SMA(8) & SMA(9) for short-term trend confirmation
Smart Money Concepts Module:
Displays BOS/CHoCH, Order Blocks, FVGs, Equal Highs/Lows, and Premium/Discount zones
🔧 Improvements & Uniqueness
Integrates Supertrend momentum with Smart Money Concepts (SMC) structural analysis.
Dual detection layers: Internal (micro) and Swing (macro) structures.
ATR-driven auto labeling for entry, stop, and profit targets.
Premium/Discount and Equilibrium zones visualized on the chart.
Built-in ADX filter to skip low-trend market conditions.
✅ Summary
Scalper Pro Pattern Recognition & Price Action merges classical trend-following with modern market structure analytics.
It combines momentum detection, volatility control, and smart money mapping into one cohesive framework.
Unified trend, structure, and risk visualization.
Auto-marked BOS/CHoCH, OB, FVG, and liquidity zones.
Usable for scalping, intraday, or swing trading setups.
⚠️ This strategy is based on historical data and designed for educational use only.
Always apply sound risk management and forward testing before live trading.
Curvature Tensor Pivots - HIVECurvature Tensor Pivots - HIVE
I. CORE CONCEPT & ORIGINALITY
Curvature Tensor Pivots - HIVE is an advanced, multi-dimensional pivot detection system that combines differential geometry, reinforcement learning, and statistical physics to identify high-probability reversal zones before they fully form. Unlike traditional pivot indicators that rely on simple price comparisons or lagging moving averages, this system models price action as a smooth curve in geometric space and calculates its mathematical curvature (how sharply the price trajectory is "bending") to detect pivots with scientific precision.
What Makes This Original:
Differential Geometry Engine: The script calculates first and second derivatives of price using Kalman-filtered trajectory analysis, then computes true mathematical curvature (κ) using the classical formula: κ = |y''| / (1 + y'²)^(3/2). This approach treats price as a physical phenomenon rather than discrete data points.
Ghost Vertex Prediction: A proprietary algorithm that detects pivots 1-3 bars BEFORE they complete by identifying when velocity approaches zero while acceleration is high—this is the mathematical definition of a turning point.
Multi-Armed Bandit AI: Four distinct pivot detection strategies (Fast, Balanced, Strict, Tensor) run simultaneously in shadow portfolios. A Thompson Sampling reinforcement learning algorithm continuously evaluates which strategy performs best in current market conditions and automatically selects it.
Hive Consensus System: When 3 or 4 of the parallel strategies agree on the same price zone, the system generates "confluence zones"—areas of institutional-grade probability.
Dynamic Volatility Scaling (DVS): All parameters auto-adjust based on current ATR relative to historical average, making the indicator adaptive across all timeframes and instruments without manual re-optimization.
II. HOW THE COMPONENTS WORK TOGETHER
This is NOT a simple mashup —each subsystem feeds data into the others in a closed-loop learning architecture:
The Processing Pipeline:
Step 1: Geometric Foundation
Raw price is normalized against a 50-period SMA to create a trajectory baseline
A Zero-Lag EMA smooths the trajectory while preserving edge response
Kalman filter removes noise while maintaining signal integrity
Step 2: Calculus Layer
First derivative (y') measures velocity of price movement
Second derivative (y'') measures acceleration (rate of velocity change)
Curvature (κ) is calculated from these derivatives, representing how sharply price is turning
Step 3: Statistical Validation
Z-Score measures how many standard deviations current price deviates from the Kalman-filtered "true price"
Only pivots with Z-Score > threshold (default 1.2) are considered statistically significant
This filters out noise and micro-fluctuations
Step 4: Tensor Construction
Curvature is combined with volatility (ATR-based) and momentum (ROC-based) to create a multidimensional "tensor score"
This tensor represents the geometric stress in the price field
High tensor magnitude = high probability of structural failure (reversal)
Step 5: AI Decision Layer
All 4 bandit strategies evaluate current conditions using different sensitivity thresholds
Each strategy maintains a virtual portfolio that trades its signals in real-time
Thompson Sampling algorithm updates Bayesian priors (alpha/beta distributions) based on each strategy's Sharpe ratio, win rate, and drawdown
The highest-performing strategy's signals are displayed to the user
Step 6: Confluence Aggregation
When multiple strategies agree on the same price zone, that zone is highlighted as a confluence area. These represent "hive mind" consensus—the strongest setups
Why This Integration Matters:
Traditional indicators either detect pivots too late (lagging) or generate too many false signals (noisy). By requiring geometric confirmation (curvature), statistical significance (Z-Score), multi-strategy agreement (hive voting), and performance validation (RL feedback) , this system achieves institutional-grade precision. The reinforcement learning layer ensures the system adapts as market regimes change, rather than degrading over time like static algorithms.
III. DETAILED METHODOLOGY
A. Curvature Calculation (Differential Geometry)
The system models price as a parametric curve where:
x-axis = time (bar index)
y-axis = normalized price
The curvature at any point represents how quickly the direction of the tangent line is changing. High curvature = sharp turn = potential pivot.
Implementation:
Lookback window (default 8 bars) defines the local curve segment
Smoothing (default 5 bars) applies adaptive EMA to reduce tick noise
Curvature is normalized to 0-1 scale using local statistical bounds (mean ± 2 standard deviations)
B. Ghost Vertex (Predictive Pivot Detection)
Classical pivot detection waits for price to form a swing high/low and confirm. Ghost Vertex uses calculus to predict the turning point:
Conditions for Ghost Pivot:
Velocity (y') ≈ 0 (price rate of change approaching zero)
Acceleration (y'') ≠ 0 (change is decelerating/accelerating)
Z-Score > threshold (statistically abnormal position)
This allows detection 1-3 bars before the actual high/low prints, providing an early entry edge.
C. Multi-Armed Bandit Reinforcement Learning
The system runs 4 parallel "bandits" (agents), each with different detection sensitivity:
Bandit Strategies:
Fast: Low curvature threshold (0.1), low Z-Score requirement (1.0) → High frequency, more signals
Balanced: Standard thresholds (0.2 curvature, 1.5 Z-Score) → Moderate frequency
Strict: High thresholds (0.4 curvature, 2.0 Z-Score) → Low frequency, high conviction
Tensor: Requires tensor magnitude > 0.5 → Geometric-weighted detection
Learning Algorithm (Thompson Sampling):
Each bandit maintains a Beta distribution with parameters (α, β)
After each trade outcome, α is incremented for wins, β for losses
Selection probability is proportional to sampled success rate from the distribution
This naturally balances exploration (trying underperformed strategies) vs exploitation (using best strategy)
Performance Metrics Tracked:
Equity curve for each shadow portfolio
Win rate percentage
Sharpe ratio (risk-adjusted returns)
Maximum drawdown
Total trades executed
The system displays all metrics in real-time on the dashboard so users can see which strategy is currently "winning."
D. Dynamic Volatility Scaling (DVS)
Markets cycle between high volatility (trending, news-driven) and low volatility (ranging, quiet). Static parameters fail when regime changes.
DVS Solution:
Measures current ATR(30) / close as normalized volatility
Compares to 100-bar SMA of normalized volatility
Ratio > 1 = high volatility → lengthen lookbacks, raise thresholds (prevent noise)
Ratio < 1 = low volatility → shorten lookbacks, lower thresholds (maintain sensitivity)
This single feature is why the indicator works on 1-minute crypto charts AND daily stock charts without parameter changes.
E. Confluence Zone Detection
The script divides the recent price range (200 bars) into 200 discrete zones. On each bar:
Each of the 4 bandits votes on potential pivot zones
Votes accumulate in a histogram array
Zones with ≥ 3 votes (75% agreement) are drawn as colored boxes
Red boxes = resistance confluence, Green boxes = support confluence
These zones act as magnet levels where price often returns multiple times.
IV. HOW TO USE THIS INDICATOR
For Scalpers (1m - 5m timeframes):
Settings: Use "Aggressive" or "Adaptive" pivot mode, Curvature Window 5-8, Min Pivot Strength 50-60
Entry Signal: Triangle marker appears (🔺 for longs, 🔻 for shorts)
Confirmation: Check that Hive Sentiment on dashboard agrees (3+ votes)
Stop Loss: Use the dotted volatility-adjusted target line in reverse (if pivot is at 100 with target at 110, stop is ~95)
Take Profit: Use the projected target line (default 3× ATR)
Advanced: Wait for confluence zone formation, then enter on retest of the zone
For Day Traders (15m - 1H timeframes):
Settings: Use "Adaptive" mode (default settings work well)
Entry Signal: Pivot marker + Hive Consensus alert
Confirmation: Check dashboard—ensure selected bandit has Sharpe > 1.5 and Win% > 55%
Filter: Only take pivots with Pivot Strength > 70 (shown in dashboard)
Risk Management: Monitor the Live Position Tracker—if your selected bandit is holding a position, consider that as market structure context
Exit: Either use target lines OR exit when opposite pivot appears
For Swing Traders (4H - Daily timeframes):
Settings: Use "Conservative" mode, Curvature Window 12-20, Min Bars Between Pivots 15-30
Focus on Confluence: Only trade when 4/4 bandits agree (unanimous hive consensus)
Entry: Set limit orders at confluence zones rather than market orders at pivot signals
Confirmation: Look for breakout diamonds (◆) after pivot—these signal momentum continuation
Risk Management: Use wider stops (base stop loss % = 3-5%)
Dashboard Interpretation:
Top Section (Real-Time Metrics):
κ (Curv): Current curvature. >0.6 = active pivot forming
Tensor: Geometric stress. Positive = bullish bias, Negative = bearish bias
Z-Score: Statistical deviation. >2.0 or <-2.0 = extreme outlier (strong signal)
Bandit Performance Table:
α/β: Bayesian parameters. Higher α = more wins in history
Win%: Self-explanatory. >60% is excellent
Sharpe: Risk-adjusted returns. >2.0 is institutional-grade
Status: Shows which strategy is currently selected
Live Position Tracker:
Shows if the selected bandit's shadow portfolio is currently holding a position
Displays entry price and real-time P&L
Use this as "what the AI would do" confirmation
Hive Sentiment:
Shows vote distribution across all 4 bandits
"BULLISH" with 3+ green votes = high-conviction long setup
"BEARISH" with 3+ red votes = high-conviction short setup
Alert Setup:
The script includes 6 alert conditions:
"AI High Pivot" = Selected bandit signals short
"AI Low Pivot" = Selected bandit signals long
"Hive Consensus BUY" = 3+ bandits agree on long
"Hive Consensus SELL" = 3+ bandits agree on short
"Breakout Up" = Resistance breakout (continuation long)
"Breakdown Down" = Support breakdown (continuation short)
Recommended Alert Strategy:
Set "Hive Consensus" alerts for high-conviction setups
Use "AI Pivot" alerts for active monitoring during your trading session
Use breakout alerts for momentum/trend-following entries
V. PARAMETER OPTIMIZATION GUIDE
Core Geometry Parameters:
Curvature Window (default 8):
Lower (3-5): Detects micro-structure, best for scalping volatile pairs (crypto, forex majors)
Higher (12-20): Detects macro-structure, best for swing trading stocks/indices
Rule of thumb: Set to ~0.5% of your typical trade duration in bars
Curvature Smoothing (default 5):
Increase if you see too many false pivots (noisy instrument)
Decrease if pivots lag (missing entries by 2-3 bars)
Inflection Threshold (default 0.20):
This is advanced. Lower = more inflection zones highlighted
Useful for identifying order blocks and liquidity voids
Most users can leave default
Pivot Detection Parameters:
Pivot Sensitivity Mode:
Aggressive: Use in low-volatility range-bound markets
Normal: General purpose
Adaptive: Recommended—auto-adjusts via DVS
Conservative: Use in choppy, whipsaw conditions or for swing trading
Min Bars Between Pivots (default 8):
THIS IS CRITICAL for visual clarity
If chart looks cluttered, increase to 12-15
If missing pivots, decrease to 5-6
Match to your timeframe: 1m charts use 3-5, Daily charts use 20+
Min Z-Score (default 1.2):
Statistical filter. Higher = fewer but stronger signals
During news events (NFP, FOMC), increase to 2.0+
In calm markets, 1.0 works well
Min Pivot Strength (default 60):
Composite quality score (0-100)
80+ = institutional-grade pivots only
50-70 = balanced
Below 50 = will show weak setups (not recommended)
RL & DVS Parameters:
Enable DVS (default ON):
Leave enabled unless you want to manually tune for a specific market condition
This is the "secret sauce" for cross-timeframe performance
DVS Sensitivity (default 1.0):
Increase to 1.5-2.0 for extremely volatile instruments (meme stocks, altcoins)
Decrease to 0.5-0.7 for stable instruments (utilities, bonds)
RL Algorithm (default Thompson Sampling):
Thompson Sampling: Best for non-stationary markets (recommended)
UCB1: Best for stable, mean-reverting markets
Epsilon-Greedy: For testing only
Contextual: Advanced—uses market regime as context
Risk Parameters:
Base Stop Loss % (default 2.0):
Set to 1.5-2× your instrument's average ATR as a percentage
Example: If SPY ATR = $3 and price = $450, ATR% = 0.67%, so use 1.5-2.0%
Base Take Profit % (default 4.0):
Aim for 2:1 reward/risk ratio minimum
For mean-reversion strategies, use 1.5-2.0%
For trend-following, use 3-5%
VI. UNDERSTANDING THE UNDERLYING CONCEPTS
Why Differential Geometry?
Traditional technical analysis treats price as discrete data points. Differential geometry models price as a continuous manifold —a smooth surface that can be analyzed using calculus. This allows us to ask: "At what rate is the trend changing?" rather than just "Is price going up or down?"
The curvature metric captures something fundamental: inflection points in market psychology . When buyers exhaust and sellers take over (or vice versa), the price trajectory must curve. By measuring this curvature mathematically, we detect these psychological shifts with precision.
Why Reinforcement Learning?
Markets are non-stationary —statistical properties change over time. A strategy that works in Q1 may fail in Q3. Traditional indicators have fixed parameters and degrade over time.
The multi-armed bandit framework solves this by:
Running multiple strategies in parallel (diversification)
Continuously measuring performance (feedback loop)
Automatically shifting capital to what's working (adaptation)
This is how professional hedge funds operate—they don't use one strategy, they use ensembles with dynamic allocation.
Why Kalman Filtering?
Raw price contains two components: signal (true movement) and noise (random fluctuations). Kalman filters are the gold standard in aerospace and robotics for extracting signal from noisy sensors.
By applying this to price data, we get a "clean" trajectory to measure curvature against. This prevents false pivots from bid-ask bounce or single-print anomalies.
Why Z-Score Validation?
Not all high-curvature points are tradeable. A sharp turn in a ranging market might just be noise. Z-Score ensures that pivots occur at statistically abnormal price levels —places where price has deviated significantly from its Kalman-filtered "fair value."
This filters out 70-80% of false signals while preserving true reversal points.
VII. COMMON USE CASES & STRATEGIES
Strategy 1: Confluence Zone Reversal Trading
Wait for confluence zone to form (red or green box)
Wait for price to approach zone
Enter when pivot marker appears WITHIN the confluence zone
Stop: Beyond the zone
Target: Opposite confluence zone or 3× ATR
Strategy 2: Hive Consensus Scalping
Set alert for "Hive Consensus BUY/SELL"
When alert fires, check dashboard—ensure 3-4 votes
Enter immediately (market order or 1-tick limit)
Stop: Tight, 1-1.5× ATR
Target: 2× ATR or opposite pivot signal
Strategy 3: Bandit-Following Swing Trading
On Daily timeframe, monitor which bandit has best Sharpe ratio over 30+ days
Take ONLY that bandit's signals (ignore others)
Enter on pivot, hold until opposite pivot or target line
Position size based on bandit's current win rate (higher win% = larger position)
Strategy 4: Breakout Confirmation
Identify key support/resistance level manually
Wait for pivot to form AT that level
If price breaks level and diamond breakout marker appears, enter in breakout direction
This combines support/resistance with geometric confirmation
Strategy 5: Inflection Zone Limit Orders
Enable "Show Inflection Zones"
Place limit buy orders at bottom of purple zones
Place limit sell orders at top of purple zones
These zones represent structural change points where price often pauses
VIII. WHAT THIS INDICATOR DOES NOT DO
To set proper expectations:
This is NOT:
A "holy grail" with 100% win rate
A strategy that works without risk management
A replacement for understanding market fundamentals
A signal copier (you must interpret context)
This DOES NOT:
Predict black swan events
Account for fundamental news (you must avoid trading during major news if not experienced)
Work well in extremely low liquidity conditions (penny stocks, microcap crypto)
Generate signals during consolidation (by design—prevents whipsaw)
Best Performance:
Liquid instruments (SPY, ES, NQ, EUR/USD, BTC/USD, etc.)
Clear trend or range conditions (struggles in choppy transition periods)
Timeframes 5m and above (1m can work but requires experience)
IX. PERFORMANCE EXPECTATIONS
Based on shadow portfolio backtesting across multiple instruments:
Conservative Mode:
Signal frequency: 2-5 per week (Daily charts)
Expected win rate: 60-70%
Average RRR: 2.5:1
Adaptive Mode:
Signal frequency: 5-15 per day (15m charts)
Expected win rate: 55-65%
Average RRR: 2:1
Aggressive Mode:
Signal frequency: 20-40 per day (5m charts)
Expected win rate: 50-60%
Average RRR: 1.5:1
Note: These are statistical expectations. Individual results depend on execution, risk management, and market conditions.
X. PRIVACY & INVITE-ONLY NATURE
This script is invite-only to:
Maintain signal quality (prevent market impact from mass adoption)
Provide dedicated support to users
Continuously improve the algorithm based on user feedback
Ensure users understand the complexity before deploying real capital
The script is closed-source to protect proprietary research in:
Ghost Vertex prediction mathematics
Tensor construction methodology
Bandit reward function design
DVS scaling algorithms
XI. FINAL RECOMMENDATIONS
Before Trading Live:
Paper trade for minimum 2 weeks to understand signal timing
Start with ONE timeframe and master it before adding others
Monitor the dashboard —if selected bandit Sharpe drops below 1.0, reduce size
Use confluence and hive consensus for highest-quality setups
Respect the Min Bars Between Pivots setting —this prevents overtrading
Risk Management Rules:
Never risk more than 1-2% of account per trade
If 3 consecutive losses occur, stop trading and review (possible regime change)
Use the shadow portfolio as a guide—if ALL bandits are losing, market is in transition
Combine with other analysis (order flow, volume profile) for best results
Continuous Learning:
The RL system improves over time, but only if you:
Keep the indicator running (it learns from bar data)
Don't constantly change parameters (confuses the learning)
Let it accumulate at least 50 samples before judging performance
Review the dashboard weekly to see which bandits are adapting
CONCLUSION
Curvature Tensor Pivots - HIVE represents a fusion of advanced mathematics, machine learning, and practical trading experience. It is designed for serious traders who want institutional-grade tools and understand that edge comes from superior methodology, not magic formulas.
The system's strength lies in its adaptive intelligence —it doesn't just detect pivots, it learns which detection method works best right now, in this market, under these conditions. The hive consensus mechanism provides confidence, the geometric foundation provides precision, and the reinforcement learning provides evolution.
Use it wisely, manage risk properly, and let the mathematics work for you.
Disclaimer: This indicator is a tool for analysis and does not constitute financial advice. Past performance of shadow portfolios does not guarantee future results. Trading involves substantial risk of loss. Always perform your own due diligence and never trade with capital you cannot afford to lose.
Taking you to school. — Dskyz, Trade with insight. Trade with anticipation.
ICT Sigma Hybrid FVGThis indicator combines three analytical components—statistical volatility modeling, ICT imbalance logic, and higher-timeframe bias filtering—to help traders interpret displacement-driven price inefficiencies. The goal is to reduce noise and highlight only meaningful FVGs that occur with sufficient volatility and directional context.
Sigma Volatility Zones
The script calculates statistically normalized deviation levels using a multi-regime standard deviation blended with ATR.
This produces adaptive volatility zones that:
Expand during trending or high-volatility periods
Contract during consolidation
Highlight extremes more accurately than fixed standard deviations
These zones help users identify where price is operating in premium/discount relative to recent volatility.
Fair Value Gaps With Displacement Scoring
Every potential FVG is evaluated using a displacement score based on candle body expansion, wick displacement, and relative move efficiency. FVGs that do not exceed the minimum score are filtered out. This ensures the script only displays gaps associated with meaningful movement, not minor pricing noise.
Optional Higher-Timeframe Bias Filter
The HTF bias engine evaluates structure using selected higher-timeframe EMAs.
When enabled, the indicator:
Shows bullish FVGs only in bullish higher-timeframe conditions
Shows bearish FVGs only in bearish conditions
Hides counter-trend FVGs that may have lower reliability
Users may disable this to see all qualifying gaps regardless of bias.
ATR-Adaptive Volatility Conditioning
ATR is blended into the model so the displacement score and sigma zones adjust automatically to sudden volatility changes such as:
Major economic releases
Earnings
High-impact market events
Overnight volatility shifts
This helps maintain consistent FVG quality during rapidly changing conditions.
How to Use the Indicator:
Use sigma levels to understand whether price is extended or discounted relative to recent volatility.
Monitor FVGs that appear within or near sigma extremes to identify potential exhaustion or continuation zones.
Combine HTF bias with LTF displacement gaps to align intraday entries with broader directional flow.
ATR-adjusted scoring helps distinguish between meaningful inefficiencies and low-quality gaps.
Example 1 — Intraday Sigma Expansion & Displacement FVG Reaction
Figure 1. Price collapses from a 4.5σ extreme during a volatility expansion event.
Only high-impact FVGs are shown due to the displacement filter, removing low-quality gaps.
Sigma bands expand dynamically as volatility increases, illustrating how the model adapts automatically.
Example 2 — Higher-Timeframe Sigma Compression After a Major Trend Leg
Figure 2. After a large macro move, sigma levels compress tightly, forming a volatility cluster.
These HTF sigma zones later act as reaction levels during continuation.
This demonstrates why the model blends HTF sigma structure with LTF displacement gaps for alignment.
Recommended Settings
Standard deviation lookback: 100
ATR length: 50
ATR blend weight: 0.5
Minimum Z-score: 1.8
Sigma levels: 1.5 / 3 / 4.5
HTF bias: Daily (optional)
FVG displacement filter: On
