Market Regime IndexThe Market Regime Index is a top-down macro regime nowcasting tool that offers a consolidated view of the market’s risk appetite. It tracks 32 of the world’s most influential markets across asset classes to determine investor sentiment by applying trend-following signals to each independent asset. It features adjustable parameters and a built-in alert system that notifies investors when conditions transition between Risk-On and Risk-Off regimes. The selected markets are grouped into equities (7), fixed income (9), currencies (7), commodities (5), and derivatives (4):
Equities = S&P 500 E-mini Index Futures, Nasdaq-100 E-mini Index Futures, Russell 2000 E-mini Index Futures, STOXX Europe 600 Index Futures, Nikkei 225 Index Futures, MSCI Emerging Markets Index Futures, and S&P 500 High Beta (SPHB)/Low Beta (SPLV) Ratio.
Fixed Income = US 10Y Treasury Yield, US 2Y Treasury Yield, US 10Y-02Y Yield Spread, German 10Y Bund Yield, UK 10Y Gilt Yield, US 10Y Breakeven Inflation Rate, US 10Y TIPS Yield, US High Yield Option-Adjusted Spread, and US Corporate Option-Adjusted Spread.
Currencies = US Dollar Index (DXY), Australian Dollar/US Dollar, Euro/US Dollar, Chinese Yuan/US Dollar, Pound Sterling/US Dollar, Japanese Yen/US Dollar, and Bitcoin/US Dollar.
Commodities = ICE Brent Crude Oil Futures, COMEX Gold Futures, COMEX Silver Futures, COMEX Copper Futures, and S&P Goldman Sachs Commodity Index (GSCI) Futures.
Derivatives = CBOE S&P 500 Volatility Index (VIX), ICE US Bond Market Volatility Index (MOVE), CBOE 3M Implied Correlation Index, and CBOE VIX Volatility Index (VVIX)/VIX.
All assets are directionally aligned with their historical correlation to the S&P 500. Each asset contributes equally based on its individual bullish or bearish signal. The overall market regime is calculated as the difference between the number of Risk-On and Risk-Off signals divided by the total number of assets, displayed as the percentage of markets confirming each regime. Green indicates Risk-On and occurs when the number of Risk-On signals exceeds Risk-Off signals, while red indicates Risk-Off and occurs when the number of Risk-Off signals exceeds Risk-On signals.
Bullish Signal = (Fast MA – Slow MA) > (ATR × ATR Margin)
Bearish Signal = (Fast MA – Slow MA) < –(ATR × ATR Margin)
Market Regime = (Risk-On signals – Risk-Off signals) ÷ Total assets
This indicator is designed with flexibility in mind, allowing users to include or exclude individual assets that contribute to the market regime and adjust the input parameters used for trend signal detection. These parameters apply to each independent asset, and the overall regime signal is smoothed by the signal length to reduce noise and enhance reliability. Investors can position according to the prevailing market regime by selecting factors that have historically outperformed under each regime environment to minimise downside risk and maximise upside potential:
Risk-On Equity Factors = High Beta > Cyclicals > Low Volatility > Defensives.
Risk-Off Equity Factors = Defensives > Low Volatility > Cyclicals > High Beta.
Risk-On Fixed Income Factors = High Yield > Investment Grade > Treasuries.
Risk-Off Fixed Income Factors = Treasuries > Investment Grade > High Yield.
Risk-On Commodity Factors = Industrial Metals > Energy > Agriculture > Gold.
Risk-Off Commodity Factors = Gold > Agriculture > Energy > Industrial Metals.
Risk-On Currency Factors = Cryptocurrencies > Foreign Currencies > US Dollar.
Risk-Off Currency Factors = US Dollar > Foreign Currencies > Cryptocurrencies.
In summary, the Market Regime Index is a comprehensive macro risk-management tool that identifies the current market regime and helps investors align portfolio risk with the market’s underlying risk appetite. Its intuitive, color-coded design makes it an indispensable resource for investors seeking to navigate shifting market conditions and enhance risk-adjusted performance by selecting factors that have historically outperformed. While it has proven historically valuable, asset-specific characteristics and correlations evolve over time as market dynamics change.
インジケーターとストラテジー
One cushion backward movement① The price breaks through the MA at the body, confirming that it is there.
② After that, a reversal candlestick is confirmed, triggering a sign and alert.
*If the reversal candlestick returns to the MA at the body, no sign or alert will be issued.
*In other words, this is Granville's guideline #2. Or #1.
Gho$t EMA CloudSimple 9/14EMA With Cloud system. Ghost EMA Cloud is a clean, minimal trend-tracking indicator designed to visualize short-term momentum shifts. It plots the 9-EMA (gray) and 14-EMA (white) while shading the area between them with dynamic cloud colors — green when momentum turns bullish, red when it weakens. The smooth cloud instantly highlights crossovers that often precede breakout or reversal moves. Optional 5-EMA and 12-EMA layers can be toggled on for extra precision without cluttering the chart. Ideal for intraday and swing traders, Ghost EMA Cloud helps you confirm entries, spot trend continuations, and time exits with clear visual simplicity and speed.
Options Levels — Call/Put Walls, Gamma Flip, Dark Gamma, WhalesOptions Levels 🎯 plots key institutional and options-based levels directly on your chart — including Call Wall, Put Wall, Gamma Flip, Dark Gamma, five Whale levels, and Sigma deviation bands (σ1/σ2).
It features elegant emoji labels, group visibility toggles, and a clean right-side extension where each line ends exactly at its label — ideal for both intraday and swing traders.
✨ Key Features
Single input with 13 ordered levels:
CallWall, PutWall, GammaFlip, DarkGamma, Whale1..Whale5, Upperσ1, Upperσ2, Lowerσ1, Lowerσ2
Expressive labels (🟢, 🔴, ⚖️, 🌑, 🐋, σ¹/σ²) designed for dark-themed charts.
Right-edge extension: each line extends precisely to its label — no infinite lines.
Visibility toggles by group:
Critical levels (Call/Put/Gamma/Dark Gamma)
Whale levels (1–5)
Sigma deviation levels
Dynamic length multipliers: emphasizes the importance of each type.
Built-in alerts for key breakouts:
Price crossing above Call Wall
Price crossing below Put Wall
⚙️ Inputs & Settings
📋 Level List (string) — a comma-separated list of 13 numerical values
Example:
🎨 Appearance
Base line length (in bars)
Show/hide labels
Line thickness
Extend line + label to the right
Bars to the right (distance between price and label)
👁️ Visibility
Toggle Critical levels
Toggle Whale levels
Toggle Sigma bands
🚀 How to Use
Paste your list of 13 levels into the input field in the correct order.
Adjust base length and line thickness to fit your timeframe.
Enable “Extend to the right” to show labels neatly past the current candle.
Use visibility toggles to focus on what matters (e.g., hide Whales for short-term trading).
Optionally, enable alerts for Call/Put Wall breakouts.
WeBull Style DashboardMimics the "Quotes" island on WeBull Desktop Application
Shows Latest price in big numbers
Open Price
High Price
Low Price
Prev. Close
52 Week High
52 Week Low
% Range (Able to be toggled from last close, or open)
Adaptive Volume Delta Map---
📊 Adaptive Volume Delta Map (AVDM)
What is Adaptive Volume Delta Map (AVDM)?
The Adaptive Volume Delta Map (AVDM) is a smart, multi-timeframe indicator that visualizes buy and sell volume imbalances directly on the chart.
It adapts automatically to the best available data resolution (tick, second, minute, or daily), allowing traders to analyze market activity with micro-level precision .
In addition to calculating volume delta (the difference between buying and selling pressure), AVDM can display a Volume Distribution Map — a per-price-level visualization showing how volume is split between buyers and sellers.
Key Features
✅ Adaptive Resolution Selection — Automatically chooses the highest possible data granularity — from tick to daily timeframe.
✅ Volume Delta Visualization — Displays delta candles reflecting the dominance of buyers (green), sellers (red), and delta (orange).
✅ Per-Level Volume Map (optional) — Shows detailed buy/sell volume distribution per price level, grouped by `Ticks Per Row`.
✅ Bid/Ask Classification — When enabled, AVDM uses bid/ask logic to classify trade direction with greater accuracy.
✅ Smart Auto-Disable Protection — Automatically disables volume map if too many price levels (>50) are detected — preventing performance degradation.
Inputs Overview
Use Seconds Resolution — Enables use of second-level data (if your TradingView subscription allows it).
Use Tick Resolution — Enables tick-based analysis for the most detailed view. If available, enable both tick and seconds resolution.
Use Bid/Ask Calculated — Uses bid/ask midpoint logic to classify trades.
Show Volume Distribution — Toggles per-price-level buy/sell volume visualization.
Ticks Per Row — Controls how many ticks are grouped per volume level. Reduce this value for finer detail, or increase it to reduce visual load.
Calculated Bars — Sets how many historical bars the indicator should process. Higher value increases accuracy but may impact performance.
How to Use
1. Add the indicator to your chart.
2. Ensure that your symbol provides volume data (and preferably tick or second-level data).
3. The indicator will automatically select the optimal timeframe for detailed calculation.
4. If your TradingView subscription allows second-level data , enable “Use Seconds Resolution.”
5. If your subscription allows tick-level data , enable both “Use Tick Resolution” and “Use Seconds Resolution.”
6. Adjust the “Calculated Bars” input to set how many historical bars the indicator should process.
7. Observe the Volume Delta Candles :
* Green = Buy pressure dominates
* Red = Sell pressure dominates
8. To see buy/sell clustering by price, enable “Show Volume Distribution.”
9. If the indicator disables the map and shows:
" Volume Distribution disabled: Too many price levels detected (>50). Try decreasing 'Ticks Per Row' or using a lower chart resolution. If you don’t care about the map, just turn off 'Show Volume Distribution'. "
— follow the instructions to reduce chart load.
Notes
* Automatically adapts to your chart’s resolution and data availability.
* If your symbol doesn’t provide volume data, a runtime warning will appear.
* Works best on futures , FX , and crypto instruments with high-frequency volume streams.
Why Traders Love It
AVDM combines adaptive resolution , volume delta analysis , and visual distribution mapping into one clean, efficient tool.
Perfect for traders studying:
* Market microstructure
* Aggressive vs. passive participation
* Volume absorption
* Order flow imbalance zones
* Delta-based divergence signals
Technical Highlights
* Built with Pine Script v6
* Adaptive resolution logic (`security_lower_tf`)
* Smart memory-safe map rendering
* Dynamic bid/ask classification
* Automatic overload protection
---
Adaptive Square Levels (Prev + Curr Month, Configurable)
The Adaptive Square Levels (Configurable Edition) indicator dynamically plots price levels based on perfect squares — a concept derived from harmonic market behavior and geometric scaling.
Each month, the script automatically detects the new monthly open and generates square levels both above and below the opening price.
This version introduces full configurability, allowing traders to adjust how many square levels they want to visualize on either side of the base level. The indicator also visually separates previous and current month levels for easy reference.
⚙️ Features
🔢 User-Configurable Range: Choose how many levels to plot above and below the base level.
🧮 Mathematically Derived Levels: Based on perfect squares up to a user-defined max price.
📅 Monthly Auto-Reset: Automatically refreshes at the start of each new month.
🎨 Color-Coded Levels:
Orange → Major levels (square roots divisible by 3)
Yellow → Regular levels
Star (★) → Base level (nearest to monthly open)
🕰️ Dual Month Display: Shows both current and previous month levels for trend comparison.
💡 How to Use
Add the indicator to any symbol and timeframe (preferably daily or higher).
Adjust:
Max Price Level → The upper bound of your price universe.
Number of Levels Each Side → Controls the density of levels.
Observe how price reacts around these mathematically significant zones.
Use in confluence with your own price action, volume, or support/resistance analysis.
📊 Ideal For
Swing traders analyzing monthly trend reversals
Price structure and geometry enthusiasts
Traders exploring market harmonics or square-of-nine–based frameworks
🧠 Note
The script doesn’t provide buy/sell signals — it offers a structural map of key levels derived from square relationships.
Use it as a visual guide to align entries and exits with natural market geometry.
MTF RSI Heatmap)# MTF RSI Heatmap — v2.7.2
**Hybrid Higher-TF Trend + Intraday Impulse Detection + Smart Counters & Alerts**
Turn your lower pane into a **multi-timeframe market bias dashboard**. This heatmap blends classic RSI momentum with a **hybrid Daily/Weekly MA-stack trend** and an **intraday impulse override** that flags fast moves *as they happen*. Clean, configurable, and built for real trading flow.
---
## What it shows
* **6 stacked rows = 6 timeframes** (bottom → top).
* **Colors**: Green = Bull, Red = Bear, Yellow = Neutral.
* **Header counter**: `Bull X/6 | Bear Y/6` = live agreement across visible rows.
* **Impulse markers** ▲/▼ on intraday rows (5m/15m/60m/240m) when a shock move triggers.
* **Signal bar**: A thin column above the top row when at least **N of 6** rows align (configurable).
---
## Why it’s different
* **Impulse Override (intraday)**
Detects sharp moves using % change over the last *N* bars, optionally gated by **volume > SMA × multiplier**. This catches dumps/pops earlier than RSI alone.
* **Hybrid D/W (structure over noise)**
Daily/Weekly rows can use an **MA stack (8/21/55)** instead of RSI for a more stable higher-timeframe trend read. Optional **price > fast MA** filter for stricter confirmation.
* **Intrabar option**
Flip rows **during the bar** for early reads (accepting repaint on TF close), or keep it close-only for no surprises.
---
## Key features
* 🌈 **Theme**: Classic or High-Contrast colors.
* 🧠 **RSI thresholds**: Bull above 55, Bear below 45 (editable).
* 🧲 **RSI smoothing** (EMA) for intraday rows to reduce flicker.
* 🧰 **Compact left legend** with adjustable text size & opacity.
* 🚨 **Alerts**:
* **Impulse-only** (per TF and “any intraday”)
* **N-of-6 confirmation** (bull/bear)
---
## Recommended settings (fast opens & news)
* **Impulse**: `Bars = 1–2`, `Threshold = 0.25–0.35%`, `Vol confirm = ON`, `Multiplier = 1.3–1.5`.
* **Hybrid D/W**: `ON`, `EMA 8/21/55`, `Price filter = ON`.
* **Intrabar**: `ON` if you want intra-bar updates (repaints at TF close).
---
## How to read it
1. **Row scan**: Are the bottom (fast) rows aligning first? That’s early momentum.
2. **Header counter**: Look for 4+/6 agreement as momentum broadens.
3. **Signal bar**: Acts as a “go/no-go” confirmation when your threshold is met.
4. **Impulse ▲/▼**: Use as a **heads-up** for acceleration; then watch if rows cascade in that direction.
---
## Alerts (exact names)
Create alerts with these built-ins:
* **Impulse UP — any intraday**
* **Impulse DOWN — any intraday**
* **Impulse UP — TF1 / TF2 / TF3 / TF4**
* **Impulse DOWN — TF1 / TF2 / TF3 / TF4**
* **Bull confirmation** (N-of-6)
* **Bear confirmation** (N-of-6)
Tip: Use **Once per bar** or **Once per bar close** depending on whether you enabled *Intrabar*.
---
## Inputs overview
* **Timeframes & visibility** per row.
* **RSI**: length, bull/bear thresholds, optional EMA smoothing (intraday only).
* **Impulse**: bars, %, volume confirm, SMA length, multiplier, markers.
* **Hybrid D/W**: MA type (EMA/SMA/HMA), 8/21/55 lengths, price filter.
* **Theme & Legend**: color theme, label size (Tiny/Small/Normal), legend opacity.
* **Signal**: N required for confirmation (default 4).
---
## Pro tips
* Combine with **session opens**, **VWAP**, and **liquidity levels**.
* If you trade breakouts, let **impulse triggers** cue attention, then wait for **N-of-6** confirmation.
* For swing bias, lean on **Hybrid D/W**—it changes slower, but with intent.
---
## Notes & limitations
* **Intrabar = repaint expected** on higher-TF closes—by design for earlier context.
* Colors/thresholds are general guidance, not signals by themselves.
* Past performance ≠ future results; **this is not financial advice**.
---
If you enjoy this, drop a ⭐ and tell me what you want next: background shading on confirmation, tooltips with RSI/ROC per row, or a MACD/RSI hybrid mode. Trade sharp! ✨
Market Pressure Differential (MPD) [SharpStrat]Market Pressure Differential (MPD)
Concept & Purpose
The Market Pressure Differential (MPD) is a proprietary indicator designed to measure the internal balance of buying and selling pressure directly on the price chart.
Unlike standard momentum or trend indicators, MPD analyzes the structural behavior of each candle—its body, wicks, and overall range—to determine whether the market is dominated by expansion (buying aggression) or contraction (selling absorption).
This indicator provides a visual overlay of market pressure that adapts dynamically to volatility, helping traders see real-time shifts in participation intensity without using oscillators.
In simple terms:
When MPD expands upward → buyer pressure dominates.
When MPD contracts downward → seller pressure dominates.
Calculation Overview
MPD uses a structural candle formula to compute directional pressure:
Body Ratio = (Close − Open) / (High − Low)
Wick Differential = (Lower Wick − Upper Wick) / (High − Low)
Raw Pressure = (Body Ratio × Body Weight) + (Wick Differential × Wick Weight)
Then it applies:
EMA smoothing (to stabilize short-term noise)
Standard deviation normalization (to maintain consistent scaling)
ATR projection (to adapt the signal visually to volatility)
This produces the MPD projection line and the pressure ribbon, drawn directly on the main chart.
Customizable Inputs
Users can adjust color schemes, EMA smoothing length, ATR parameters, normalization length, and body/wick weighting to adapt the indicator’s sensitivity and aesthetic to different markets or chart themes.
How to Use
The Market Pressure Differential (MPD) visualizes the real-time balance between buying and selling pressure. It should be used as a contextual bias tool, not a standalone signal generator.
The white line represents the MPD projection, showing how market pressure evolves in real time based on candle structure and volatility.
The red line represents the ATR envelope, which defines the market’s expected volatility range.
MPD reacts quickly to candle structure, so trend bias is based on how its projection behaves relative to the ATR envelope:
Above the ATR band → positive pressure and bullish bias.
Below the ATR band → negative pressure and bearish bias.
Hovering near the ATR band → neutral or indecisive conditions.
The MPD percentage in the label represents the normalized strength of pressure relative to recent volatility.
Positive % = buying dominance.
Negative % = selling dominance.
Higher absolute values = stronger momentum compared to volatility.
To trade with MPD:
Watch candle colors and the projection line — green or positive % shows buyer control, red or negative % shows seller control.
Note transitions above or below the ATR level for early signs of momentum shifts.
Combine MPD signals with price structure, key levels, or volume for confirmation.
This helps reveal which side controls the market and whether that pressure is strong enough to overcome typical volatility.
Disclaimer
It introduces a novel structural–pressure approach to visualizing market dynamics.
For educational and analytical purposes only; this does not constitute financial advice.
SPX Option Wedge Breakout v1.5a (Dual + Micro)
# SPX Option Wedge Breakout (Dual + Micro) — by Miguel Licero
What it does
This indicator is designed to catch fast, 3–5-bar momentum bursts in **SPX options (OPRA)** or the underlying (SPX/ES). It combines two detection engines:
1. Wedge Breakout Engine
Locates *falling-wedge* compression using recent swing pivots and verifies statistical tightness (channel width vs. ATR).
Confirms breakout when price closes above the wedge’s upper guide **and** above **EMA-21**, with optional **VWAP** confluence and volume expansion.
2. Micro-Breakout Engine (sub-VWAP thrusts)
Triggers when **EMA-9 crosses above EMA-21** and price **breaks the prior N-bar high (BOS)** with volume expansion.
Specifically handles rallies that start **below VWAP**, requiring sufficient “room to VWAP” measured as a fraction of ATR.
This indicador provides a state machine overlay and a dashboard . Consider the following states:
IDLE – no setup
WATCH – valid compression + preconditions (OBV positive, RSI build zone, tightness)
TRIGGER-A – breakout *above VWAP* (Strict mode)
TRIGGER-B/Micro – Under VWAP thrust with room to VWAP or Micro-Breakout (Flexible mode - this is the most common case for SPX options)
Why I believe it works
In my observation i've found short, violent option moves often occur when:
(1) liquidity compresses then releases (wedge), or
(2) micro momentum flips under VWAP and snaps to VWAP/EMA-50 (delta + IV expansion).
The indicator surfaces these two structures with clear, tradeable signals.
---
Inputs (key parameters)
EMAs : 9 / 21 / 50 / 200 (trend/micro-momentum and magnets/targets)
VWAP: optional intraday confluence and distance metric
Wedge: pivot widths (`left/right`), `tightK` (channel width vs ATR), `atrLen`
Volume/OBV/RSI: `volLen`, `volBoost` (volume expansion factor), `obvLen` (slope via linreg), `rsiLen`
VWAP Mode:
Strict – breakout must be above VWAP (TRIGGER-A)
Flexible – allows under VWAP breakouts if there’s room to VWAP (`minVWAPDistATR`) or a Micro-Breakout
Micro-Breakout: `useMicro`, `bosLen` (BOS lookback), `minRSIMicro`
Impulse Bars Target: time-based exit helper (e.g., like 3 or 5 candles)
---
Plots & UI
Overlay: EMA-9/21/50/200, VWAP, wedge guides, **TRIGGER** marker
Background color: state shading (IDLE / WATCH / TRIGGER)
Dashboard (table, top-right): State, VWAP mode, distances to VWAP/EMA-50/EMA-200, EMA-stack (9 vs 21), OBV slope sign, RSI zone, Tightness flag, Impulse counter, Micro status (9>21 / +BOS)
---
Alerts
Consider these status when you see them:
WATCH (there is wedge ready) – compression + preconditions met (prepare the order)
TRIGGER-A (price going above VWAP) – Strict breakout confirmation
TRIGGER-B/Micro – Flexible breakout (price under VWAP with room to go up to VWAP, EMA 200, -OB, resistance line, etc) or Micro-Breakout
---
Recommended Use
Timeframes: 1-minute for execution, 5-minute for context.
Symbols : OPRA SPX options (0-DTE/1-DTE) or SPX/ES for confirmation.
Sessions: Intraday with visible session (VWAP requires intraday data).
Suggested presets (for options):
`VWAP Mode = Flexible`
`minVWAPDistATR = 0.7` (room to VWAP)
`tightK = 1.0–1.2` (compression sensitivity)
`volBoost = 1.2` (raise to 1.3–1.4 if noisy)
`obvLen = 14–20` (14 = more reactive)
`Impulse Bars = 5`
High-probability windows (ET): 11:45–12:45, 13:45–15:15, 15:00–15:45.
---
Notes & Limitations
Designed to surface setups , not to replace discretion. Combine with your risk plan.
VWAP “room” is statistical; on news/latency spikes, distances may be crossed in one bar.
Works on underlyings too, but option % moves are what this study targets.
It's not guaranteed to work 100% of the times. Trade responsibly.
---
조건 검색식//@version=5
indicator("조건 검색식", overlay=true)
// ----------------------
// 기본 입력
// ----------------------
shortEmaLen = input.int(112, "단기 EMA")
midEmaLen = input.int(224, "중기 EMA")
longEmaLen = input.int(448, "장기 EMA")
ema5Len = input.int(5, "EMA 5")
ema20Len = input.int(20, "EMA 20")
bbLen = input.int(20, "볼린저 기간")
bbMult = input.float(2.0, "볼린저 배수")
// ----------------------
// 이동평균선
// ----------------------
emaShort = ta.ema(close, shortEmaLen)
emaMid = ta.ema(close, midEmaLen)
emaLong = ta.ema(close, longEmaLen)
ema5 = ta.ema(close, ema5Len)
ema20 = ta.ema(close, ema20Len)
// ----------------------
// 거래량 / 거래대금
// ----------------------
avgVol = ta.sma(volume, 5)
cond_vol = (volume >= 50000 and volume <= 99999999)
cond_val = (avgVol * close >= 50000 and avgVol * close <= 9999999)
// ----------------------
// 캔들 비교
// ----------------------
cond_price = (close < close) // 1봉전 종가 < 현재 종가
// ----------------------
// 이평 조건
// ----------------------
cond_ma_reverse = (emaShort < emaMid and emaMid < emaLong) // 역배열
cond_ma_short = (ema5 > ema20 and ema5 > ema20 ) // 1봉 이상 지속
// ----------------------
// 체결강도 (추정치, 거래량 기준)
// ----------------------
// 체결강도 공식은 증권사마다 다르므로 근사치로 가정: (상승 거래량 비중/총거래량)
// TradingView에서 직접적인 "체결강도"는 제공하지 않음 → 임시로 100% 충족으로 세팅
cond_strength = true // 혹은 커스텀 계산 가능
// ----------------------
// 볼린저밴드 조건
// ----------------------
basis = ta.sma(close, bbLen)
dev = ta.stdev(close, bbLen)
bbUpper = basis + bbMult * dev
// 종가가 상단선 -5% ~ +5% 이내
cond_bb = (close >= bbUpper * 0.95 and close <= bbUpper * 1.05)
// ----------------------
// 일목균형표 (9,26,52)
// ----------------------
conversion = (ta.highest(high,9) + ta.lowest(low,9)) / 2
base = (ta.highest(high,26) + ta.lowest(low,26)) / 2
span1 = (conversion + base) / 2
span2 = (ta.highest(high,52) + ta.lowest(low,52)) / 2
cond_ichimoku = (close > span1 and close > span2)
// ----------------------
// 최종 조건
// ----------------------
condition = cond_vol and cond_val and cond_price and cond_ma_reverse and cond_ma_short and cond_strength and cond_bb and cond_ichimoku
plotshape(condition, title="조건 충족", style=shape.labelup, color=color.green, size=size.small, text="조건OK")
Volume Bubbles & Liquidity Heatmap 30% + biasLuxAlgo gave us an open script, I just primmed it up with the use of Chat GPT:There is no single magic number (like “delta must be 800”) that will guarantee directional follow-through in every market. But you can make a mathematically rigorous filter that gives you a high-probability test — by normalizing the delta against that market’s typical behavior and requiring multiple confirmations. Below is a compact, actionable algorithm you can implement immediately (in your platform or spreadsheet) plus concrete thresholds and the math behind them.
High-IQ rule set (math + trade logic)
Use three independent checks. Only take the trade if ALL three pass.
1) Z-score (statistical significance of the delta)
Compute rolling mean
𝜇
μ and std dev
𝜎
σ of delta on the same timeframe (e.g. 5m) over a lookback window
𝑊
W (suggest
𝑊
=
50
W=50–200 bars).
𝑍
=
delta
bar
−
𝜇
𝑊
𝜎
𝑊
Z=
σ
W
delta
bar
−μ
W
Threshold: require
𝑍
≥
2.5
Z≥2.5 (strong) — accept 2.0 for less strict, 3.0 for very rare signals.
Why: a Z>=2.5 means this delta is an outlier (~<1% one-sided), not normal noise.
2) Relative Imbalance (strength vs total volume)
Compute imbalance ratio:
𝑅
=
∣
delta
bar
∣
volume
bar
R=
volume
bar
∣delta
bar
∣
Threshold: require
𝑅
≥
0.25
R≥0.25 (25% of the bar’s volume is one-sided). For scalping you can tighten to 0.30–0.40.
Why: a big delta with tiny volume isn’t meaningful; this normalizes to participation.
3) Net follow-through over a confirmation window
Look ahead
𝑁
N bars (or check the next bar if you need intrabar speed). Compute cumulative delta and price move:
cum_delta
𝑁
=
∑
𝑖
=
1
𝑁
delta
bar
+
𝑖
cum_delta
N
=
i=1
∑
N
delta
bar+i
price_move
=
close
bar
+
𝑁
−
close
bar
price_move=close
bar+N
−close
bar
Thresholds: require
cum_delta
𝑁
cum_delta
N
has the same sign as the trigger and
∣
cum_delta
𝑁
∣
≥
0.5
×
∣
delta
bar
∣
∣cum_delta
N
∣≥0.5×∣delta
bar
∣, and
price_move
price_move exceeds a minimum meaningful tick amount (instrument dependent). For ES / US30 type futures: price move ≥ 5–10 ticks; for forex pairs maybe 10–20 pips? Use ATR
20
20
×0.05 as a generic minimum.
Why: separates immediate absorption (buy delta then sellers soak it) from genuine continuation.
Bonus check — Structural context (must be satisfied)
Trigger should not occur against a strong structural barrier (VWAP, daily high/low, previous session POC) unless you’re explicitly trading exhaustion/absorption setups.
If signal occurs near resistance and price does not clear that resistance within
𝑁
N bars, treat as probable trap.
Putting it together — final trade decision
Take the long (example):
If
𝑍
≥
2.5
Z≥2.5 and
𝑅
≥
0.25
R≥0.25 and cum_delta_N confirms and no hard resistance above (or you’re willing to trade absorption), then enter.
Place stop: under the low of the last 2–3 bars or X ATR (instrument dependent).
Initial target: risk:reward 1:1 minimum, scale out at 1.5–2R after confirming further delta.
Concrete numeric illustration using your numbers
You saw FOL = 456, then sell reaction with ~350 opposite. How to interpret:
Suppose your 5-min rolling mean
𝜇
μ = 100 and
𝜎
σ=120 (example):
𝑍
=
(
456
−
100
)
/
120
≈
2.97
⇒
statistically big
Z=(456−100)/120≈2.97⇒statistically big
So it passes Z.
If volume on that bar = 2000 contracts:
𝑅
=
456
/
2000
=
0.228
⇒
just below 0.25 threshold
R=456/2000=0.228⇒just below 0.25 threshold
So it fails R (weak participation proportionally), explaining why 456 alone didn’t move price.
Seller came back with 350 opposite soon after — check cum_delta_N:
cum_delta
𝑛
𝑒
𝑥
𝑡
3
≈
456
−
350
=
106
net
cum_delta
next3
≈456−350=106 net
Net is small relative to the initial spike — not convincing follow-through.
Conclusion: despite a big absolute number (456), relative measures and lack of follow-through meant the move failed. That’s exactly why raw numbers alone are unreliable.
Advanced refinement (for elite performance)
Use rolling median + MAD instead of mean/std if delta distribution is skewed.
Scale Z by volume volatility: divide Z by
volume
bar
/
volume
‾
volume
bar
/
volume
to penalize low-volume bars.
Use a signed cumulative delta over micro-windows: compute windowed cumulative delta standardized:
𝑍
cum
=
∑
𝑖
=
0
𝑀
−
1
delta
𝑡
−
𝑖
−
𝑀
𝜇
𝑀
𝜎
Z
cum
=
M
σ
∑
i=0
M−1
delta
t−i
−Mμ
and require
𝑍
cum
≥
3
Z
cum
≥3 for very high confidence.
Add market-depth / DOM confirmation (if available): require that resting ask size above is less than resting bid size below by a factor (i.e. visible liquidity supports the move).
Practical thresholds to start with (tune per instrument)
Lookback
𝑊
W: 100 bars (5m → about a trading day)
Z threshold: 2.5
Imbalance ratio
𝑅
R: ≥ 0.25 (tighten to 0.30 for scalping)
Confirmation window
𝑁
N: next 1–3 bars for intraday scalps; 3–6 bars for short swings
Cum delta confirmation: ≥ 0.5 × initial delta and same sign
Price move confirmation: ≥ 0.03 × ATR20 (or set absolute ticks per instrument)
TL;DR — the single best rule
Don’t chase absolute numbers. Use Z-score of delta + delta/volume ratio + real follow-through. If all three align, odds are heavily in your favor.
If you want, I can:
give you a tiny script (pseudocode or Pine / Python) that computes Z, R, cum_delta_N and flags qualifying bars, or
run the calculation on a sample of your recent bars if you paste a small CSV of time, delta, volume, close.
Which do you want? (I’ll give code right away.)
You said:
give me a percentage of difference where we have a high probability
ChatGPT said:
Thought for 7s
Nice — straight to the point. Here’s a concise, practical set of percentage thresholds (and associated confidence estimates) you can use right now to flag a “high probability” delta signal. I’ll give you three tiers (good / strong / elite), explain what each means, show how to compute it, and give a short example using your 456/2000 bar.
One-line rule
Compute delta percent
𝑃
=
∣
delta
∣
volume
×
100
%
P=
volume
∣delta∣
×100%.
Then require Z-score of delta ≥ 2.5 and P to be at or above the threshold below for the desired confidence tier.
Threshold tiers (percent of bar volume)
Good (high-probability trade candidate)
P ≥ 20–25%
Typical success probability (when combined with Z≥2.5 and no hard structural resistance): ~60–70%.
Use when you want a steady flow of signals with decent edge.
Strong (high confidence)
P ≥ 30–35%
Typical success probability: ~70–80% (with Z≥2.5 + structural alignment).
Fewer signals, higher win-rate. Good default for intraday.
Elite (very high probability / low false positives)
P ≥ 40–50%
Typical success probability: ~80–90% (with Z≥3 and confirmation).
Rare signals. Use for meaningful size or when you need maximum certainty.
Why percentage matters (short)
Absolute delta (456) is meaningless without volume context. A 456 delta on 2,000 volume → P = 456/2000 = 22.8% → sits just below the Good threshold, which matches why it failed: decent but not dominant participation.
Additional required checks (don’t skip these)
To turn P into a reliable filter, always require:
Z-score of the delta ≥ 2.5 (or ≥3 for Elite signals).
No immediate structural barrier (VWAP, strong resistance) that would plausibly absorb the order.
Follow-through: within next N bars (N = 1–3 for scalps) price moves in the same direction by ≥ 0.03×ATR20 (or instrument-specific tick threshold). If this fails, cut fast.
Combine all three and your realized win-rate will approach the probabilities above.
Practical quick checklist (to apply each signal)
Compute P = |delta|/volume. Is P ≥ 30%? (or your chosen tier)
Compute Z = (delta − mean)/std over last 100 bars. Is Z ≥ 2.5?
Is price not pinned under a heavy resistance?
Enter on next bar close (or intrabar on continuation), stop under last 2-bar low (for longs).
If price fails to move ≥ 0.03×ATR20 within 3 bars, exit.
Example (your bar)
delta = 456, volume = 2000 → P = 22.8% → below Good threshold (25%).
Even if Z was high, P failed — explains the failure. You need P ≥ ~30% plus Z≥2.5 to call it a Strong signal.
Final notes (instrument & timeframe)
These percentages were calibrated for futures/US indices and short intraday bars (1–5m).
For FX or low-tick instruments, use absolute ticks + a smaller P threshold (start at 15–20%).
Always backtest on the specific instrument/timeframe and tune thresholds.
If you want, I’ll generate a tiny script (Python or Pine) that calculates P and Z and flags Good/Strong/Elite signals for your chart history so you can see exact historical hit rates. Which language (Python or Pine)?
You said:
so if we have 456 g vs 350 r what pct is that in favour of green?
ChatGPT said:
Perfect — let’s calculate it carefully, digit by digit so we don’t make a slip.
We have:
Green (buy) volume = 456
Red (sell) volume = 350
We want to know what percentage is in favor of green, relative to the total volume.
Step 1. Compute total volume
Total
=
456
+
350
=
806
Total=456+350=806
Step 2. Compute green’s share
\text{Green %} = \frac{456}{806} \times 100
Now do it precisely:
456
÷
806
=
0.565506
456÷806=0.565506 (rounded)
So:
0.565506
×
100
=
56.55
%
0.565506×100=56.55%
Step 3. Compute red’s share (for context)
350
806
=
0.434494
→
43.45
%
806
350
=0.434494→43.45%
Step 4. Compute difference (bias toward green)
56.55
%
−
43.45
%
=
13.10
%
56.55%−43.45%=13.10%
✅ Final answer:
Green = 56.6% of total
Red = 43.4% of total
Bias = +13.1 percentage points in favor of green
So that’s only a 13% advantage to buyers — modest pressure, not a dominant imbalance.
For a high-probability signal (as we discussed earlier), you generally want ≥30% imbalance (e.g. ~65/35 split or stronger).
Original:
''The Volume Bubbles & Liquidity Heatmap indicator is a powerful trading tool designed to give traders a clearer picture of volume dynamics and liquidity distribution across multiple timeframes. By combining dynamic volume bubbles with a liquidity heatmap, this indicator makes it easy to identify areas of price interest, spot market imbalances, and improve decision-making for both scalpers and swing traders.
This trading indicator is ideal for volume traders, price action traders, and liquidity-focused traders who need a clean, multi-dimensional view of buyer/seller activity and the zones where market participants are most active. With full customization over bubble display, timeframes, and visual settings, traders can tailor the tool to fit virtually any trading strategy or market.''
LA - MACD EMA BandsOverview of the "LA - MACD EMA Bands" Indicator
For Better view, use this indicator along with "LA - EMA Bands with MTF Dashboard"
The "LA - MACD EMA Bands" is a custom technical indicator written in Pine Script v6 for TradingView. It builds on the traditional Moving Average Convergence Divergence (MACD) oscillator by incorporating additional smoothing via Exponential Moving Averages (EMAs) and Bollinger Bands (BB) applied directly to the MACD line. This creates a multi-layered momentum and volatility tool displayed in a separate pane below the price chart (not overlaid on the price itself).
The indicator allows for customization, such as selecting a different timeframe (for multi-timeframe analysis) and adjusting period lengths. It fetches data from the specified timeframe using request.security with lookahead enabled to avoid repainting issues. The core idea is to provide insights into momentum trends, crossovers, and volatility expansions/contractions in the MACD's behavior, making it suitable for identifying potential trend reversals, continuations, or ranging markets.
Unlike a standard MACD, which focuses primarily on momentum via a single line, signal line, and histogram, this version emphasizes longer-term smoothing and volatility boundaries. It uses visual fills between lines to highlight bullish/bearish conditions, aiding quick interpretation. Below, I'll break down each component, its calculation, visual representation, and practical uses.
Detailed Breakdown of Each Component and Its Uses
MACD Line (Blue Line, Labeled 'MACD Line')
Calculation: This is the core MACD value, computed as the difference between a fast EMA (default length 12) and a slow EMA (default length 144) of the input source (default: close price). The EMAs are calculated on data from the selected timeframe.
Visuals: Plotted as a solid blue line.
Uses:
Measures momentum: When above zero, it indicates bullish momentum (prices rising faster in the short term); below zero, bearish momentum.
Trend identification: Rising MACD suggests strengthening uptrends; falling suggests downtrends.
Divergence spotting: Compare with price action—e.g., if price makes higher highs but MACD makes lower highs, it signals potential bearish reversal (and vice versa for bullish divergence).
In trading: Often used for entry/exit signals when crossing the zero line or other lines in the indicator.
MACD EMA (Red Line, Labeled 'MACD EMA')
Calculation: A 12-period EMA applied to the MACD Line itself.
Visuals: Plotted as a solid red line.
Uses:
Acts as a signal line for the MACD, smoothing out short-term noise.
Crossover signals: When the MACD Line crosses above the MACD EMA, it can signal a bullish buy opportunity; crossing below suggests a bearish sell.
Trend confirmation: Helps filter false signals in choppy markets by requiring confirmation from this slower-moving average.
In trading: Useful for momentum-based strategies, like entering trades on crossovers in alignment with the overall trend.
Fill Between MACD Line and MACD EMA (Green/Red Shaded Area, Titled 'MACD Fill')
Calculation: The area between the MACD Line and MACD EMA is filled with color based on their relative positions.
Color Logic: Green (with 57% transparency) if MACD Line > MACD EMA (bullish); red if MACD Line < MACD EMA (bearish).
Visuals: Semi-transparent fill for easy visibility without overwhelming the lines.
Uses:
Quick visual cue for momentum shifts: Green areas highlight bullish phases; red for bearish.
Enhances readability: Makes crossovers more apparent at a glance, especially in fast-moving markets.
In trading: Can be used to time entries/exits or as a filter (e.g., only take long trades in green zones).
Bollinger Bands on MACD (BB Upper: Black Dotted, BB Basis: Maroon Dotted, BB Lower: Black Dotted)
Calculation: Bollinger Bands applied to the MACD Line.
BB Basis: 144-period EMA of the MACD Line.
BB Standard Deviation: 144-period stdev of the MACD Line.
BB Upper: BB Basis + (2.0 * BB Stdev)
BB Lower: BB Basis - (2.0 * BB Stdev)
Visuals: Upper and lower bands as black dotted lines; basis as maroon dotted
Uses:
Volatility measurement: Bands expand during high momentum volatility (strong trends) and contract during low volatility (ranging or consolidation).
Mean reversion: When MACD Line touches or exceeds the upper band, it may signal overbought conditions (potential sell); lower band for oversold (potential buy).
Squeeze detection: Narrow bands (squeeze) often precede big moves—watch for breakouts.
In trading: Combines momentum with volatility; e.g., a MACD Line breakout above the upper band could confirm a strong uptrend.
BB Basis EMA (Green Line, Labeled 'BB Basis EMA')
Calculation: A 72-period EMA applied to the BB Basis (which is already a 144-period EMA of the MACD Line).
Visuals: Solid green line.
Uses:
Further smoothing: Provides a longer-term view of the MACD's average behavior, reducing noise from the BB Basis.
Trend direction: Acts as a baseline for the BB system—above it suggests bullish bias in momentum volatility; below, bearish.
Crossover with BB Basis: Can signal shifts in volatility trends (e.g., BB Basis crossing above BB Basis EMA indicates increasing bullish volatility).
In trading: Useful for confirming longer-term trends or as a filter for BB-based signals.
Fill Between BB Basis and BB Basis EMA (Gray Shaded Area, Titled 'BB Basis Fill')
Calculation: The area between BB Basis and BB Basis EMA is filled.
Color Logic: Currently set to a constant semi-transparent gray regardless of position.
Visuals: Semi-transparent gray fill.
Uses:
Highlights divergence: Shows when the shorter-term BB Basis deviates from its longer-term EMA, indicating potential volatility shifts.
Visual aid for crossovers: Makes it easier to spot when BB Basis crosses its EMA.
In trading: Could be used to identify overextensions in volatility (e.g., wide gray areas might signal impending mean reversion).
Zero Line (Black Horizontal Line)
Calculation: A simple horizontal line at y=0.
Visuals: Solid black line.
Uses:
Reference point: Divides bullish (above) from bearish (below) territory for all MACD-related lines.
In trading: Crossovers of the zero line by the MACD Line or BB Basis can signal major trend changes.
How It Differs from a Normal MACD
A standard MACD (e.g., the built-in TradingView MACD with defaults 12/26/9) consists of:
MACD Line: EMA(12) - EMA(26).
Signal Line: EMA(MACD Line, 9).
Histogram: MACD Line - Signal Line (bars showing convergence/divergence).
Key differences in "LA - MACD EMA Bands":
Periods: Uses a much longer slow EMA (144 vs. 26), making it more sensitive to long-term trends but less reactive to short-term price action. The MACD EMA is 12 periods (vs. 9), further emphasizing smoothing.
No Histogram: Replaces the histogram with fills and bands for visual emphasis on crossovers and volatility.
Added Bollinger Bands: Applies BB directly to the MACD Line (with a long 144-period basis), introducing volatility analysis absent in standard MACD. This helps detect "squeezes" or expansions in momentum.
Additional EMA Layer: The BB Basis EMA (72-period) adds a secondary smoothing level to the BB system, providing a hierarchical view of momentum (short-term MACD → mid-term BB → long-term EMA).
Multi-Timeframe Support: Built-in option for higher timeframes, unlike basic MACD.
Focus: Standard MACD is purely momentum-focused; this version integrates volatility (via BB) and multi-layer smoothing, making it better for trend-following in volatile markets but potentially overwhelming for beginners.
Overall, this indicator transforms the MACD from a simple oscillator into a comprehensive momentum-volatility hybrid, reducing false signals in trending markets but introducing lag.
Overall Pros and Cons
Pros:
Enhanced Visualization: Fills and bands make trends, crossovers, and volatility easier to spot without needing multiple indicators.
Reduced Noise: Longer periods (144, 72) smooth out whipsaws, ideal for swing or position trading in trending assets like stocks or forex.
Volatility Integration: BB adds a dimension not in standard MACD, helping identify breakouts or consolidations.
Customizable: Inputs for timeframes and lengths allow adaptation to different assets/timeframes.
Multi-Layered Insights: Combines short-term signals (MACD crossovers) with long-term confirmation (BB EMA), improving signal reliability.
Cons:
Lagging Nature: Long periods (e.g., 144) delay signals, missing early entries in fast markets or leading to late exits.
Complexity: Multiple lines and fills can clutter the pane, requiring experience to interpret; beginners might misread it.
Potential Overfitting: Custom periods (12/144/12/144/72) may work well on historical data but underperform in live trading without backtesting.
No Built-in Alerts/Signals: Relies on visual interpretation; users must manually set alerts for crossovers.
Resource Intensive: On lower timeframes or with lookahead, it might slow chart loading on Trading View.
This indicator shines in strategies combining momentum and volatility, like trend-following with BB squeezes, but test it on your assets (e.g., via backtesting) to ensure it fits your style.
For Better view, use this indicator along with "LA - EMA Bands with MTF Dashboard"
5, 10, 15, 20 SMA//@version=5
indicator("5, 10, 15, 20 SMA", overlay=true)
// 이평선 정의
sma5 = ta.sma(close, 5)
sma10 = ta.sma(close, 10)
sma15 = ta.sma(close, 15)
sma20 = ta.sma(close, 25)
// 차트에 표시
plot(sma5, color=color.red, linewidth=2, title="5 SMA")
plot(sma10, color=color.orange, linewidth=2, title="10 SMA")
plot(sma15, color=color.yellow, linewidth=2, title="15 SMA")
plot(sma20, color=color.green, linewidth=2, title="20 SMA")
Smooth Cloud Trend Filter (20/50 EMA)The Smooth Cloud indicator visualizes market trend direction using two Exponential Moving Averages (EMAs): a Fast EMA (20-period) and a Slow EMA (50-period).
The area between these averages forms a shaded cloud that changes color according to the trend bias:
🟢 Green Cloud: Fast EMA is above the Slow EMA → Bullish trend.
🔴 Red Cloud: Fast EMA is below the Slow EMA → Bearish trend.
On this chart, the cloud remains green for most of the period, reflecting a strong and persistent uptrend.
During minor pullbacks, the transitions stay smooth, showing that the trend filter reacts steadily without excessive noise.
Price action consistently holds above the cloud from late September through early October, indicating sustained buyer control and bullish momentum.
This view focuses solely on the trend structure provided by the Smooth Cloud.
While other modules of the full system (such as the RSI Liquidity Spectrum and Zig Zag++ Volume Profile) add momentum and liquidity context, the Smooth Cloud alone highlights clear directional bias and trend strength.
When the price trades above a green cloud, traders often look for long opportunities on pullbacks or RSI confirmations.
A red cloud flip would signal a possible trend reversal or weakening momentum, suggesting short setups instead.
The thickness of the cloud also offers visual insight — thicker clouds indicate stronger trend momentum, while thinner ones suggest consolidation or indecision.
📊 High/Low Daily & Weekly + Internal [Premium v2]📊 High/Low Daily & Weekly + Internal
Easily visualize the most important price levels on any market with this professional tool.
✨ Features:
🔹 Previous Day High/Low (red/green)
🔹 Current Day Internal High/Low (orange/yellow)
🔹 Previous Week High/Low (blue/aqua) – visible on all timeframes, including 1-minute
⚙️ Extras:
✅ Toggle buttons to show/hide each level type
✅ Optional labels with exact price values
✅ Customizable colors, thickness & transparency
✅ Works perfectly for identifying support, resistance, and liquidity zones
Ideal for scalpers and intraday traders who need clear structure, precision, and visual confidence on their charts.
London Breakout Structure by Ale📈 London Breakout Structure by Ale
This indicator identifies market structure breakouts (CHOCH/BOS) within a specific London session window, highlighting potential breakout trades with automatic entry, stop loss (SL), and take profit (TP) levels.
It helps traders focus on high-probability breakouts when volatility increases after the Asian session, using price structure, ATR-based volatility filters, and a custom risk/reward setup.
🔹 Example of Strategy Application
Define your session (e.g. 04:00 to 05:00).
Wait for a CHOCH (Change of Character) inside this session.
If a bullish CHOCH occurs → go LONG at candle close.
If a bearish CHOCH occurs → go SHORT at candle close.
SL is set below/above the previous swing using ATR × multiplier.
TP is calculated automatically based on your R:R ratio.
📊 Example:
When price breaks above the last swing high within the session, a “BUY” label appears and the indicator draws Entry, SL, and TP levels automatically.
If the breakout fails and price closes below the opposite structure, a “SELL” signal will replace the bullish setup.
🔹 Details
The logic is based on structural shifts (CHOCH/BOS):
A CHOCH occurs when price breaks and closes beyond the most recent high/low.
The indicator dynamically detects these shifts in structure, validating them only inside your chosen time window (e.g. the London Open).
The ATR filter ensures setups are valid only when the range has enough volatility, avoiding false signals in low-volume hours.
You can also visualize:
The session area (purple background)
Entry, Stop Loss, and Take Profit levels
Direction labels (BUY/SELL)
ATR line for volatility context
🔹 Configuration
Start / End Hour: define your preferred trading window.
ATR Length & Multiplier: adjust for volatility.
Risk/Reward Ratio: set your desired R:R (default 1:2).
Minimum Range Filter: avoids signals with tight SLs.
Alerts: receive notifications when breakout conditions occur.
🔹 Recommendations
Works best on 15m or 5m charts during London session.
Designed for breakout and structure-based traders.
Works on Forex, Crypto, and Indices.
Ideal as a visual and educational tool for understanding BOS/CHOCH behavior.
Institutional Activity DetectorInstitutional Activity Detector - Complete Tutorial
Table of Contents
Installation
Understanding the Indicator
Signal Interpretation
Settings Configuration
Trading Strategies
Best Practices
Common Mistakes to Avoid
1. Installation {#installation}
Step-by-Step Setup:
Step 1: Access TradingView
Go to TradingView.com
Log in to your account (free account works fine)
Step 2: Open Pine Editor
Click on "Pine Editor" at the bottom of the chart
If you don't see it, go to the top menu and select "Pine Editor"
Step 3: Add the Script
Click "New" to create a new indicator
Delete any default code
Copy the entire Institutional Activity Detector code
Paste it into the editor
Step 4: Save and Apply
Click "Save" (give it a name like "Inst Detector")
Click "Add to Chart"
The indicator will now appear on your chart
2. Understanding the Indicator {#understanding}
What It Detects:
This indicator identifies institutional traders (banks, hedge funds, market makers) by analyzing:
Volume Analysis
Detects unusual volume spikes that indicate large players entering
Compares current volume to 20-period average
Institutional trades create volume 2-5x normal levels
Order Flow
Delta: Difference between buying and selling volume
Positive delta = More buying pressure
Negative delta = More selling pressure
Institutions leave "footprints" in order flow
Price Action Patterns
Bullish Rejection Wicks:
| <- Small upper wick
|
███ <- Small body
███
|
|
| <- Large lower wick (rejection)
Indicates institutions bought aggressively at lower prices
Bearish Rejection Wicks:
|
|
| <- Large upper wick (rejection)
|
███ <- Small body
███
| <- Small lower wick
Indicates institutions sold aggressively at higher prices
Liquidity Grabs
Institutions often:
Push price above resistance or below support
Trigger stop losses (grab liquidity)
Reverse direction and trade the other way
Dark Pool Activity
Large block trades executed off-exchange:
High volume with minimal price movement
Indicates institutional accumulation/distribution without moving price
3. Signal Interpretation {#signals}
Signal Types:
🟢 INSTITUTIONAL BUY Signal
Appears as green triangle below candle with strength number (2-5)
What it means:
Institutions are actively accumulating (buying)
Higher strength = More confirmation factors
Strength Levels:
2-3: Moderate confidence - Wait for confirmation
4: High confidence - Strong institutional interest
5: Maximum confidence - Multiple factors aligned
🔴 INSTITUTIONAL SELL Signal
Appears as red triangle above candle with strength number (2-5)
What it means:
Institutions are actively distributing (selling)
Higher strength = More confirmation factors
🟠 Dark Pool (DP) Marker
Small orange diamond
What it means:
Large block trade executed
Accumulation/distribution happening quietly
Often precedes significant moves
Liquidity Zones
Red boxes above price = Resistance/sell liquidity
Green boxes below price = Support/buy liquidity
Institutions target these zones to trigger stops
4. Settings Configuration {#settings}
Recommended Settings by Asset Type:
For Stocks (SPY, AAPL, TSLA):
Volume Spike Multiplier: 2.0
Volume Average Period: 20
Delta Threshold: 70%
Minimum Signal Strength: 3
Timeframe: 5m, 15m, 1H
For Forex (EUR/USD, GBP/USD):
Volume Spike Multiplier: 1.5
Volume Average Period: 30
Delta Threshold: 65%
Minimum Signal Strength: 3
Timeframe: 15m, 1H, 4H
For Crypto (BTC, ETH):
Volume Spike Multiplier: 2.5
Volume Average Period: 20
Delta Threshold: 70%
Minimum Signal Strength: 4
Timeframe: 15m, 1H, 4H
For Futures (ES, NQ):
Volume Spike Multiplier: 2.0
Volume Average Period: 20
Delta Threshold: 75%
Minimum Signal Strength: 3
Timeframe: 5m, 15m, 30m
Parameter Explanations:
Volume Spike Multiplier (1.0 - 10.0)
Lower = More sensitive (more signals, some false)
Higher = Less sensitive (fewer signals, more reliable)
Start with 2.0 and adjust based on your asset's volatility
Delta Threshold % (50 - 100)
Measures buying vs selling pressure
70% = Strong institutional bias required
Lower for ranging markets, higher for trending
Minimum Signal Strength (2 - 5)
Number of factors that must align for a signal
2 = Very sensitive (many signals)
5 = Very conservative (rare signals)
Recommended: 3-4 for balance
5. Trading Strategies {#strategies}
Strategy 1: Liquidity Grab Reversal
Setup:
Price approaches a liquidity zone (green/red box)
Price penetrates the zone briefly
Institutional BUY/SELL signal appears
Price reverses away from the zone
Entry:
Enter on the signal candle close
Or wait for next candle confirmation
Stop Loss:
Below the liquidity grab low (for buys)
Above the liquidity grab high (for sells)
Take Profit:
2:1 or 3:1 risk/reward ratio
Or next opposing liquidity zone
Example:
Price drops below support → Triggers stops →
Institutional BUY signal (4-5 strength) →
Enter LONG → Price rallies
Strategy 2: Trend Continuation
Setup:
Identify the trend (higher highs/higher lows for uptrend)
Wait for pullback to support in uptrend
Institutional BUY signal appears during pullback
Confirms institutions are adding to positions
Entry:
Enter on signal with strength ≥ 4
Or next candle after signal
Stop Loss:
Below the pullback low + small buffer
Take Profit:
Previous swing high
Or trailing stop using ATR
Strategy 3: Dark Pool Accumulation
Setup:
Dark Pool (DP) markers appear multiple times
Price consolidates in tight range
Institutional BUY signal with high strength appears
Breakout occurs
Entry:
Enter on breakout candle after signal
Or on retest of breakout level
Stop Loss:
Below consolidation range
Take Profit:
Measured move (height of consolidation projected)
Strategy 4: Divergence Play
Setup:
Price makes lower low
MFI/RSI makes higher low (bullish divergence)
Institutional BUY signal appears
Volume confirms with spike
Entry:
Enter on signal candle or next
Stop Loss:
Below the divergence low
Take Profit:
Previous swing high or resistance
6. Best Practices {#best-practices}
✅ DO's:
1. Use Multiple Timeframes
Check higher timeframe for trend direction
Trade signals that align with higher timeframe
Example: 15m signals in direction of 1H trend
2. Combine with Key Levels
Support/resistance
Supply/demand zones
Previous day high/low
Round numbers (psychological levels)
3. Wait for Confirmation
Don't rush into trades
Let the signal candle close
Watch next candle for follow-through
4. Check the Metrics Table
Look at Relative Volume (should be >2.0)
Check Delta % (should be strong positive/negative)
Verify Order Flow aligns with signal
5. Consider Market Context
News events can override signals
Low liquidity times (lunch, overnight) less reliable
Major economic releases need caution
6. Paper Trade First
Test the indicator for 2-4 weeks
Learn how it behaves on your chosen assets
Develop confidence before using real money
Best Times to Trade:
Stock Market Hours:
9:30-11:30 AM EST (high volume, strong moves)
2:00-4:00 PM EST (institutional positioning)
Avoid: 11:30 AM-2:00 PM (lunch, low volume)
Forex:
London Open: 3:00-6:00 AM EST
New York Open: 8:00-11:00 AM EST
London/NY Overlap: 8:00 AM-12:00 PM EST
Crypto:
24/7 market, but highest volume during US/European hours
Watch for weekend low liquidity
7. Common Mistakes to Avoid {#mistakes}
❌ DON'T:
1. Trade Every Signal
Not all signals are equal
Focus on strength 4-5 signals
Wait for optimal setups
2. Ignore Market Structure
Don't buy into strong downtrends (catch falling knife)
Don't sell into strong uptrends (fight the tape)
Respect major support/resistance
3. Use Too Small Timeframes
1m and 2m charts are too noisy
Minimum recommended: 5m for scalping
Better: 15m, 30m, 1H for reliability
4. Overtrade
Quality over quantity
2-5 good trades per day is excellent
Forcing trades leads to losses
5. Ignore Risk Management
Always use stop losses
Risk only 1-2% per trade
Don't revenge trade after losses
6. Trade During Low Volume
Signals less reliable with low volume
Check Relative Volume metric (should be >1.5)
Avoid pre-market/after-hours for stocks
7. Misread Liquidity Grabs
Not every wick is a liquidity grab
Need volume confirmation
Must have institutional signal
Advanced Tips:
Filtering False Signals:
Use Signal Strength Filter:
Minimum strength 3 = Balanced
Minimum strength 4 = Conservative (recommended)
Minimum strength 5 = Ultra conservative
Confluence Checklist:
Signal strength ≥ 4
Relative volume > 2.0
At key support/resistance
Aligns with higher timeframe trend
Delta % strongly positive/negative
Clean price action setup
If 4+ boxes checked = High probability trade
Setting Up Alerts:
Click the three dots on the indicator
Select "Create Alert"
Choose condition:
"Institutional Buy Signal"
"Institutional Sell Signal"
"Dark Pool Activity"
Set up notification (email, SMS, app)
Save alert
Alert Strategy:
Set minimum strength to 4 for fewer, better alerts
Use for assets you can't watch constantly
Don't rely solely on alerts - check chart context
Practice Exercise:
Week 1-2: Observation
Add indicator to your favorite assets
Watch how signals develop
Note which ones lead to profitable moves
Don't trade yet - just observe
Week 3-4: Paper Trading
Use TradingView's paper trading
Trade only strength 4-5 signals
Record results in a journal
Note: entry, exit, profit/loss, what worked/didn't
Week 5+: Small Live Positions
Start with smallest position size
Trade only your best setups
Gradually increase size as you gain confidence
Keep detailed journal
Quick Reference Card:
Signal Quality Ranking:
🔥 Best Setups (Take These):
Strength 5 + Liquidity grab + Key level
Strength 4-5 + Volume >3.0 + Trend alignment
Dark Pool markers + Strength 4+ signal
✅ Good Setups:
Strength 4 at support/resistance
Strength 3-4 with strong delta
Liquidity grab + Strength 3+
⚠️ Caution (Wait for More):
Strength 2-3 in middle of nowhere
Against higher timeframe trend
Low volume (Rel Vol <1.5)
❌ Avoid:
Strength 2 only
During major news
Low liquidity hours
Against strong trend
Troubleshooting:
"Too many signals"
→ Increase Minimum Signal Strength to 4
→ Increase Volume Spike Multiplier to 2.5-3.0
"Too few signals"
→ Decrease Minimum Signal Strength to 2-3
→ Decrease Volume Spike Multiplier to 1.5
"Signals not working"
→ Check if you're trading during low volume hours
→ Verify you're using recommended timeframes
→ Make sure signals align with market structure
"Can't see liquidity zones"
→ Enable "Show Liquidity Zones" in settings
→ Adjust Swing Detection Length (try 7-15)
Resources for Further Learning:
Concepts to Study:
Order Flow Trading
Market Profile / Volume Profile
Smart Money Concepts (SMC)
Liquidity Sweeps and Stop Hunts
Institutional Order Flow
Wyckoff Method
Volume Spread Analysis (VSA)
Recommended Practice:
Study past signals on chart
Replay market using TradingView's bar replay feature
Join trading communities to share setups
Keep a detailed trading journal
Final Thoughts:
This indicator is a tool, not a crystal ball. It identifies high-probability setups where institutions are active, but still requires:
Proper risk management
Market context understanding
Patience and discipline
Continuous learning
Success Formula:
Right Tool + Proper Training + Risk Management + Discipline = Consistent Profits
Start slow, master the basics, and gradually increase complexity as you gain experience.
Good luck and trade smart! 📊📈
Aggression Bulbs v3.1 (Sessions + Bias, fixed)EYLONAggression Bulbs v3.2 (Sessions + Bias + Volume Surge)
This indicator highlights aggressive buy and sell activity during the London and New York sessions, using volume spikes and candle body dominance to detect institutional momentum.
⚙️ Main Logic
Compares each candle’s volume vs average volume (Volume Surge).
Checks body size vs full candle range to detect strong directional moves.
Uses an EMA bias filter to align signals with the current trend.
Displays green bubbles for aggressive buyers and red bubbles for aggressive sellers.
🕐 Sessions
London: 08:00–12:59 UTC+1
New York: 14:00–18:59 UTC+1
(Backgrounds: Yellow = London, Orange = New York)
📊 How to Read
🟢 Green bubble below bar → Aggressive BUY candle (strong demand).
🔴 Red bubble above bar → Aggressive SELL candle (strong supply).
Bubble size = relative strength (volume × candle dominance).
Use in confluence with key POI zones, volume profile, or delta clusters.
⚠️ Tips
Use on 1m–15m charts for scalping or intraday analysis.
Combine with your session bias or FVG zones for higher accuracy.
Set alerts when score ≥ threshold to catch early momentum.
Triple Gaussian Smoothed Ribbon [BOSWaves]Triple Gaussian Smoothed Ribbon – Adaptive Gaussian Framework
Overview
The Triple Gaussian Smoothed Ribbon is a next-generation market visualization framework built on the principles of Gaussian filtering - a mathematical model from digital signal processing designed to remove noise while preserving the integrity of the underlying trend.
Unlike conventional moving averages that suffer from phase lag and overreaction to volatility spikes, Gaussian smoothing produces a symmetrical, low-lag curve that isolates meaningful directional shifts with exceptional clarity.
Developed under the Adaptive Gaussian Framework, this indicator extends the classical Gaussian model into a multi-stage smoothing and visualization system. By layering three progressive Gaussian filters and rendering their interactions as a gradient-based ribbon field, it translates market energy into a coherent, visually structured trend environment. Each ribbon layer represents a progressively smoothed component of price motion, producing a high-fidelity gradient field that evolves in sync with real-time trend strength and momentum.
The result is a uniquely fluid trend and reversal detection system - one that feels organic, adapts seamlessly across timeframes, and reveals hidden transitions in market structure long before traditional indicators confirm them.
Theoretical Foundation
The Gaussian filter, derived from the Gaussian function developed by Carl Friedrich Gauss in 1809, operates on the principle of weighted symmetry, assigning higher importance to central price data while tapering influence toward historical extremes following a bell-curve distribution. This symmetrical design minimizes phase distortion and smooths without introducing lag spikes — a stark contrast to exponential or linear filters that sacrifice temporal accuracy for responsiveness.
By cascading three Gaussian stages in sequence, the indicator creates a multi-frequency decomposition of price action:
The first stage captures immediate trend transitions.
The second absorbs mid-term volatility ripples.
The third stabilizes structural directionality.
The final composite ribbon reflects the market’s dominant frequency - a smoothed yet reactive trend spine - while an independent, heavier Gaussian smoothing serves as a reference layer to gauge whether the primary motion leads or lags relative to broader market structure.
This multi-layered Gaussian framework effectively replicates the behavior of a signal-processing filter bank: isolating meaningful cyclical movements, suppressing random noise, and revealing phase shifts with minimal delay.
How It Works
Triple Gaussian Core
Price data is passed through three successive Gaussian smoothing stages, each refining the trend further and removing higher-frequency distortions.
The result is a fluid, continuously adaptive baseline that responds naturally to directional changes without overshooting or flattening key inflection points.
Adaptive Ribbon Architecture
The indicator visualizes its internal dynamics through a five-layer gradient ribbon. Each layer represents a progressively delayed Gaussian curve, creating a color field that dynamically shifts between bullish and bearish tones.
Expanding ribbons indicate accelerating momentum and trend conviction.
Compressing ribbons reflect consolidation and volatility contraction.
The smooth color gradient provides a real-time depiction of energy buildup or dissipation within the trend, making it visually clear when the market is entering a state of expansion, transition, or exhaustion.
Momentum-Weighted Opacity
Ribbon transparency adjusts according to normalized momentum strength.
As trend force builds, colors intensify and layers become more opaque, signifying conviction.
When momentum wanes, ribbons fade - an early visual cue for potential reversals or pauses in trend continuation.
Candle Gradient Integration
Optional candle coloring ties the chart’s candles to the prevailing Gaussian gradient, allowing traders to view raw price action and smoothed wave dynamics as a unified system.
This integration produces a visually coherent chart environment that communicates directional intent instantly.
Signal Detection Logic
Directional cues emerge when the smoother, broader Gaussian curve crosses the faster-reacting Gaussian line, marking structural inflection points in the filtered trend.
Bullish shifts : short-term momentum transitions upward through the long-term baseline after a localized trough.
Bearish shifts : momentum declines through the baseline following a local peak.
To maintain integrity in choppy markets, the framework applies a trend-strength and separation filter, which blocks weak or overlapping conditions where movement lacks conviction.
Interpretation
The Triple Gaussian Smoothed Ribbon provides a layered, intuitive read on market structure:
Trend Continuation : Expanding ribbons with deep color intensity confirm directional strength.
Reversal Phases : Color gradients flip direction, indicating a phase shift or exhaustion point.
Compression Zones : Tight, pale ribbons reveal equilibrium phases often preceding breakouts.
Momentum Divergence : Fading color intensity despite continued price movement signals weakening conviction.
These transitions mirror the natural ebb and flow of market energy - captured through the Gaussian filter’s ability to represent smooth curvature without distortion.
Strategy Integration
Trend Following
Engage during strong directional expansions. When ribbons widen and color gradients intensify, the trend is accelerating with high confidence.
Reversal Identification
Monitor for full gradient inversion and fading momentum opacity. These conditions often precede transitional phases and early reversals.
Breakout Anticipation
Flat, compressed ribbons signal low volatility and energy buildup. A sudden gradient expansion with renewed opacity confirms breakout initiation.
Multi-Timeframe Alignment
Use higher timeframes to establish directional bias and lower timeframes for entry during compression-to-expansion transitions.
Technical Implementation Details
Triple Gaussian Stack : Sequential smoothing stages produce low-lag, high-purity signals.
Adaptive Ribbon Rendering : Five-layer Gaussian visualization for gradient-based trend depth.
Momentum Normalization : Opacity dynamically tied to trend strength and volatility context.
Consolidation Filter : Suppresses false signals in low-energy or range-bound conditions.
Integrated Candle Mode : Optional color synchronization with underlying gradient flow.
Alert System : Built-in notifications for bullish and bearish transitions.
This structure blends the precision of digital signal processing with the readability of visual market analysis, creating a clean but information-rich framework.
Optimal Application Parameters
Asset Recommendations
Cryptocurrency : Higher smoothing and sigma for stability under volatility.
Forex : Balanced parameters for cycle identification and reduced noise.
Equities : Moderate Gaussian length for responsive yet stable trend reads.
Indices & Futures : Longer smoothing periods for structural confirmation.
Timeframe Recommendations
Scalping (1 - 5m) : Use shorter smoothing for fast reactivity.
Intraday (15m - 1h) : Mid-length Gaussian chain for balance.
Swing (4h - 1D) : Prioritize clarity and opacity-driven trend phases.
Position (Daily - Weekly) : Longer smoothing to capture macro rhythm.
Performance Characteristics
Most Effective In :
Trending markets with recurring volatility cycles.
Transitional phases where early directional confirmation is crucial.
Less Effective In:
Ultra-low volume markets with erratic tick data.
Random, micro-chop conditions with no structural flow.
Integration Guidelines
Pair with volatility or volume expansion tools for enhanced breakout confirmation.
Use ribbon compression to anticipate volatility shifts.
Align entries with gradient expansion in the dominant color direction.
Scale position size relative to opacity strength and ribbon width.
Disclaimer
The Triple Gaussian Smoothed Ribbon – Adaptive Gaussian Framework is designed as a signal visualization and trend interpretation tool, not a standalone trading system. Its accuracy depends on appropriate parameter tuning, contextual confirmation, and disciplined risk management. It should be applied as part of a comprehensive technical or algorithmic trading strategy.
Risk Recommender — (Heatmap)📊 Risk Recommender — Per-Trade & Annualized (Heatmap Columns)
Estimate the optimal risk percentage for any market regime.
This tool dynamically recommends how much of your account equity to risk — either per trade or at a portfolio (annualized) level — using volatility as the guide.
⚙️ How it works
Two distinct modes give you flexibility:
1️⃣ Per-Trade (ATR-based)
• Calculates the current Average True Range (ATR) compared to its long-term baseline.
• When volatility is high (ATR ↑), risk per trade decreases to maintain constant dollar risk.
• When volatility is low (ATR ↓), risk per trade increases within your defined floor and ceiling.
• The display is normalized by stop distance (× ATR) and smoothed to avoid noise.
2️⃣ Annualized (Volatility Targeting)
• Computes realized volatility (standard deviation of log returns) and an EWMA forecast of future volatility.
• Blends current and forecast volatilities to estimate “effective” volatility.
• Scales your base risk so that portfolio volatility converges toward your chosen annual target (e.g., 20%).
• Useful for portfolio-level or systematic strategies that maintain constant volatility exposure.
🎨 Heatmap Visualization
The vertical column graph acts like a thermometer:
• 🟥 Red → “Reduce risk” (volatility high).
• 🟩 Green → “Increase risk” (volatility low).
• Smoothed and bounded between your Floor and Ceiling risk levels.
• Optional dotted guides mark those bounds.
• Label shows the current mode, recommended risk %, and key metrics (ATR ratio or effective volatility).
🔧 Key Inputs
• Base max risk per trade (%) — your normal per-trade risk budget.
• ATR length / Baseline ATR length — control sensitivity to short- vs. long-term volatility.
• Target annualized volatility (%) — portfolio volatility target for quant mode.
• λ (lambda) — smoothing factor for the EWMA volatility forecast (0.90–0.99 typical).
• Floor & Ceiling — clamps the output to avoid extreme sizing.
• Smoothing & Hysteresis — prevent rapid changes in risk recommendations.
🧮 Interpreting the Output
• “Recommended Risk (%)” = suggested portion of equity to risk on the next trade (or current exposure).
• In Per-Trade mode: reflects current ATR ÷ baseline ATR .
• In Annualized mode: reflects target volatility ÷ effective volatility .
• Use the color and height of the column as a quick visual cue for aggressiveness.
💡 Typical Use Cases
• Position-sizing overlay for discretionary traders.
• Volatility-targeting component for algorithmic or multi-asset systems.
• Educational tool to understand how volatility governs prudent risk management.
📘 Notes
• This indicator provides risk suggestions only ; it does not place trades.
• Works on any symbol or timeframe.
• Combine with your own strategy or alerts for full automation.
• All calculations use built-in Pine functions; no proprietary logic.
Tags:
#RiskManagement #ATR #Volatility #Quant #PositionSizing #SystematicTrading #AlgorithmicTrading #Portfolio #TradingStrategy #Heatmap #EWMA #Risk
Trader Assistant 2Title
Trader Assistant 2 — Multi‑Timeframe ATR Volatility and Intrabar Range Monitor
Summary
Trader Assistant 2 is a compact, multi‑timeframe dashboard that helps you instantly gauge market conditions across 1m, 5m, 15m, 30m, 1h, and 4h. It blends two ATR‑based views:
- Volatility regime: current ATR vs its baseline (ATR moving average).
- Intrabar range usage: how much of ATR the current bar has already traveled from its open.
Each timeframe is color‑coded by the worst of the two signals, so you see risk and heat at a glance. An optional lead cell summarizes active alerts and lists the timeframes that triggered them.
What you see on the chart
- Single‑row table positioned at the bottom‑right of the chart.
- One cell per enabled timeframe:
- Green (soft): normal conditions
- Orange: elevated risk/volatility
- Red: high/critical risk/volatility
- Text turns white when a warning/critical condition is present
- Optional “alert” cell on the left:
- Yellow when any warning is present
- Red when any critical condition is present
- Message indicates which timeframes fired due to Volatility and/or ATR usage (e.g., “Volatility (5m, 15m) | ATR (1m)”)
How it works (high level)
- Volatility regime: compares current ATR to a smoothed ATR baseline. If the ratio exceeds your Elevated or High thresholds, the timeframe escalates to orange or red.
- Intrabar ATR usage: measures absolute distance from the bar’s open. If the move exceeds your Yellow or Red percentage of ATR, the timeframe escalates accordingly.
- Combined color: the cell shows the highest severity between the two checks.
Mermaid (logic overview)
flowchart LR
A --> B
B --> C
C --> D{Vol Severity(Normal/Elevated/High)}
E --> F
F --> G{ATR Usage Severity(Normal/Yellow/Red)}
D --> H
G --> H
H --> I
H --> J
Inputs and defaults
- Timeframe toggles: 1m, 5m, 15m, 30m, 1h, 4h (enable/disable any mix)
- ATR periods per timeframe (defaults):
- 1m: 60
- 5m: 24
- 15m: 16
- 30m: 14
- 1h: 12
- 4h: 12
- ATR baseline smoothing:
- Moving average period: 20 (used to compare current ATR vs average)
- Volatility thresholds (percent of baseline):
- Elevated: 80%
- High: 120%
- Intrabar ATR usage thresholds:
- Yellow: 50% of ATR
- Red: 75% of ATR
Typical use cases
- Session open scan: Quickly see where heat is building and which timeframes require caution.
- News and high‑impact events: Identify heightened conditions before entering or managing positions.
- Trade filtering: Avoid entries during red conditions or tighten risk; favor normal/green regimes for cleaner structure.
- Risk sizing: Reduce size or switch to passive management when multiple timeframes show elevated/high conditions.
Tips and best practices
- Threshold tuning: Different markets/venues need different percentages. Start with defaults, then adjust to your symbol’s volatility.
- Baseline smoothing: Increase the MA period to reduce noise in the volatility regime.
- Multi‑TF alignment: When higher timeframes turn orange/red, treat lower‑TF signals with extra caution.
- Combine with structure and volume tools for a complete decision framework.
Notes and limitations
- Visual monitor: This is an on‑chart dashboard/visual alert. It does not emit TradingView alert() notifications.
- Multi‑timeframe behavior: Values update according to each source timeframe’s bar closes.
- Strategy‑agnostic: This does not generate buy/sell signals. Use it for context, regime awareness, and risk control.
- Educational only: Not financial advice. Always backtest and validate on your own instruments.
Color legend
- Green: Normal conditions
- Orange: Elevated volatility and/or significant intrabar range usage
- Red: High/critical conditions (exercise caution)
- Yellow alert cell: Warning present in at least one timeframe
- Red alert cell: Critical condition present in at least one timeframe
Quick start
1) Add the indicator to your chart.
2) Enable the timeframes relevant to your trading horizon.
3) Keep defaults or tune ATR periods and thresholds to your symbol.
4) Read the row from left to right: alert cell (if present), then timeframes. Prioritize management when you see orange/red, and be selective with entries during heat.
CVD Pro – Smart Overlay + Signals (with Persist Mode)What this Indicator Does
CVD Pro visualizes Cumulative Volume Delta (CVD) data directly on your main price chart — helping you detect real buying vs. selling pressure in real time.
Unlike most CVD scripts that run in a separate subwindow, this one overlays price-mapped CVD curves on the candles themselves for better confluence with market structure and FVG zones.
The script dynamically scales normalized CVD values to the price range and uses adaptive smoothing and deviation bands to highlight shifts in trader behavior.
It also includes automatic bullish/bearish crossover signals, displayed as on-chart labels.
⚙️ Main Features
✅ Price-mapped CVD Overlay
CVD is normalized (Z-score) and projected onto the price chart for easy visual correlation with price structure.
✅ Multi-Timeframe Presets
Three sensitivity presets optimized for different chart environments:
Strict (4H) → Best for macro trends and high-timeframe structure.
Balanced (1H / 30m) → Great for active swing setups.
Sensitive (15m) → Captures short-term intraday reversals.
✅ Dynamic Bands & Smoothing
Deviation bands visualize statistical extremes in delta pressure — helping to identify exhaustion and divergence points.
✅ Smart Buy/Sell Signal Logic
Automatic label triggers when the CVD Overlay crosses its smoothed baseline:
🟢 BULL LONG → Rising CVD above the mean (buyers in control).
🔴 BEAR SHORT → Falling CVD below the mean (sellers in control).
✅ Persist Mode
Toggle to keep the last signal visible until a new one forms — ideal for traders who prefer clean chart annotations without noise.
✅ Clean, Minimal Overlay
Everything happens directly on your chart — no extra windows, no clutter. Designed for use with Smart Money Concepts, Fair Value Gaps (FVGs), or volume imbalance setups.
🧩 Use Case
CVD Pro is designed for traders who:
Use Smart Money Concepts (SMC) or ICT-style trading
Watch for FVG reactions, breaker blocks, and liquidity sweeps
Need to confirm order flow direction or momentum strength
Trade intraday or swing setups with precision entries and clear bias confirmation
⚡ Recommended Settings
4H / 1H: Use Strict mode for major structure and confirmation.
1H / 30m: Balanced mode for clear mid-term trend alignment.
15m: Sensitive mode to catch scalps and lower-TF shifts.
🧠 Pro Tips
Combine with RSI or Market Structure Breaks (MSS) for additional confluence.
A strong CVD divergence near a key FVG or 0.5–0.705 Fibonacci zone often signals reversal.
Persistent CVD crossover + price structure break = high-probability entry.
🧩 Credits
Created by Patrick S. ("Nova Labs")
Concept inspired by professional order-flow analytics and adaptive Z-Score normalization.
Would you like me to write a shorter “public summary” paragraph (for the short description at the top of TradingView, the one-liner users see before expanding)?
It’s usually a 2–3 sentence hook like:
“Overlay-based CVD indicator that merges volume delta with price structure. Detect true buying/selling pressure using adaptive normalization, deviation bands, and clean bullish/bearish crossover signals.”