Bitcoin/USDT Dominance Ratio | Astral Vision Bitcoin/USDT Dominance Ratio | Astral Vision 🌠💠
USDT dominance measures the share of total crypto market capitalization held in Tether.
When USDT dominance is high, capital is parked in stablecoins: risk appetite is low and dry powder is accumulating.
When USDT dominance is low, capital has rotated into risk assets: stablecoin supply relative to the market has been deployed.
Dividing Bitcoin's price by USDT dominance produces a ratio that amplifies both conditions: it rises when BTC appreciates while stablecoin dominance contracts (maximum risk-on), and falls when BTC depreciates while stablecoin dominance expands (maximum risk-off).
The ratio acts as a liquidity-adjusted price: a measure of how much Bitcoin is worth relative to the available pool of sidelined capital.
Calculation ⚙️
`Ratio = BTC Price / USDT Dominance (%)`
Both the ratio candles and the price chart candles are colored identically by the same threshold logic, so the regime read is simultaneously visible in the indicator panel and on the price chart without switching focus.
Plots 📊
Ratio candles in the indicator panel, colored by active regime
Oversold threshold line (positive color) and overbought threshold line (negative color)
Price chart candle coloring by the same regime logic
Background highlight on the price chart when either threshold is breached
Inputs 🎛️
`Oversold Threshold`: ratio level below which the signal enters accumulation territory (default 2100)
`Overbought Threshold`: ratio level above which the signal enters distribution territory (default 27000)
Colors 🎨
5 Astral Vision presets + custom override. Default: Infinito. Positive color activates below the oversold threshold; negative color activates above the overbought threshold.
Purpose 🎯
Tracking BTC price and USDT dominance as separate charts requires constant context-switching and leaves the relationship between the two implicit. Most dominance indicators plot stablecoin share in isolation with no connection to price magnitude, while raw BTC price charts carry no information about the liquidity environment surrounding each move.
This indicator fuses the two into a single ratio that makes the liquidity context inseparable from price. A BTC rally with contracting USDT dominance reads as a structurally stronger move than the same price gain with stable or rising stablecoin dominance and this indicator makes that difference directly visible through threshold crossings, candle color, and background regime highlighting on the price chart.
Disclaimer ⭕️
It is not financial advice, not an investment recommendation, and not affiliated with any financial institution, research firm, or organization of any kind. All content is provided for educational and informational purposes only. Always conduct your own research before making any financial decision. Indicator
MVRV Z-Score Bands | Astral Vision MVRV Z-Score Bands | Astral Vision 💠🌠
Market Value to Realized Value (MVRV) measures the ratio between Bitcoin's market capitalization and its Realized Capitalization, the aggregate value of all coins priced at their last on-chain movement.
When market cap significantly exceeds realized cap, the network is collectively sitting on large unrealized profits, historically a condition associated with distribution tops.
When the two converge or invert, the network is near or below its aggregate cost basis, the condition that has defined every major accumulation floor.
This indicator standardizes MVRV using the full historical standard deviation of market cap, producing a Z-Score that makes cycle extremes statistically comparable across all of Bitcoin's history. It then inverts the Z-Score thresholds back through the MVRV formula to project them as dynamic price levels directly onto the price chart, converting abstract statistical levels into concrete price bands that move in real time with Realized Cap.
Calculation ⚙️
`MVRV Z-Score = (Market Cap − Realized Cap) / StdDev(Market Cap, all-time)`
The standard deviation is computed over the entire available history of market cap using a growing array, ensuring the normalization reflects the full distribution of Bitcoin's market structure at every point in time.
The price bands invert the Z-Score threshold back to price:
`Band Price = BTC Price × ((target_Z × StdDev + Realized Cap) / Market Cap)`
This back-projection means the overbought and oversold bands on the price chart represent exactly the price at which the MVRV Z-Score would equal the user-defined threshold given current on-chain conditions.
Plots 📊
MVRV Z-Score line in the indicator panel, colored by active regime
Overbought threshold line (negative color) and oversold threshold line (positive color) in the panel
Dynamic overbought price band projected on the price chart (negative color, linewidth 3)
Dynamic oversold price band projected on the price chart (positive color, linewidth 3)
Background highlight on the price chart when price breaches either band
Inputs 🎛️
`Oversold Value (Z-Score)`: lower threshold defining the accumulation extreme (default −0.2)
`Overbought Value (Z-Score)`: upper threshold defining the distribution extreme (default 6.0)
`Background Transparency`: opacity of the price chart background highlight when a band is breached (default 50)
Colors 🎨
5 Astral Vision presets + custom override. Default: Paradiso. Positive color applies at oversold extremes; negative color applies at overbought extremes.
Purpose 🎯
Standard MVRV Z-Score implementations display only the oscillator panel, requiring the trader to mentally translate Z-Score levels back to price, a calculation that changes every day as Realized Cap evolves. Threshold lines in the panel are static and offer no direct price context.
This indicator closes that gap entirely. The Z-Score thresholds are continuously inverted to their equivalent price levels and projected as live bands on the chart, so the distance between current price and each extreme is always immediately readable without any mental conversion. As Realized Cap grows with each market cycle, the bands self-adjust upward, reflecting the structural elevation of Bitcoin's cost basis over time and keeping the signal relevant across every cycle without any manual recalibration.
Disclaimer ⭕️
It is not financial advice, not an investment recommendation, and not affiliated with any financial institution, research firm, or organization of any kind. All content is provided for educational and informational purposes only. Always conduct your own research before making any financial decision. Indicator
Anchored Volume Weighted Average Price | Astral Vision Anchored Volume Weighted Average Price | Astral Vision 🌠💠
The Volume Weighted Average Price anchored to a fixed date represents the average price at which every Bitcoin has changed hands since that moment, weighted by volume.
Unlike a moving average which weights bars equally by time an anchored VWAP weights each bar by its trading activity, making it a true reflection of the average cost basis for all market participants who entered after the anchor point.
When price trades above an anchored VWAP, the aggregate of participants since that anchor is in profit. When price trades below it, they are in loss.
This makes anchored VWAPs among the most reliable dynamic support and resistance levels available, as they represent the price at which the largest volume of participants is either defending a gain or protecting against a loss.
This indicator plots up to 16 simultaneous anchored VWAPs: one per calendar year from 2013 through 2025, plus three fully custom anchors at any user-defined date, all on the price chart with individual color control and labeled at the current bar.
Calculation ⚙️
`VWAP = Cumulative(HLC3 × Volume) / Cumulative(Volume)`
Accumulation begins on the first bar of the anchor year (or the exact timestamp for custom anchors) and runs continuously to the present bar. Each VWAP is computed independently, carrying its own cumulative price-volume and volume sums from its respective start date.
Plots 📊
Up to 13 year-anchored VWAP lines (2013–2025), each with a dual-layer glow (linewidths 6/2, transparency 80/0)
3 custom timestamp-anchored VWAP lines with the same glow rendering
Labeled endpoints at the current bar for every active VWAP, showing year or custom identifier
Inputs 🎛️
`2013` through `2025` :individual toggles to enable each year-anchored VWAP, each with its own color picker
`Custom 1 / 2 / 3`: toggles for three free-anchor VWAPs, each with a date/time input and color picker
Colors 🎨
Each VWAP line has its own independent color, pre-assigned along a spectral progression from violet (2013) through the visible spectrum to yellow (2025), giving each cycle year a visually distinct identity at a glance. Custom anchors default to blue, yellow, and green with full override available.
Purpose 🎯
Standard VWAP tools on PulseWire anchor to the current session or a single user-defined point, offering no way to compare multiple historical anchors simultaneously. Traders who want to assess confluence across different cycle entry points must place and manage anchors manually, one at a time.
This indicator solves that entirely: all major Bitcoin calendar years are available as one-click toggles, letting you layer any combination of historical cost bases onto the chart instantly. The custom anchors extend this to any structurally significant date (cycle lows, halving events, ETF approvals) without any manual drawing tool interaction. Confluence zones where multiple VWAPs converge are immediately visible and have historically acted as the strongest support and resistance levels in Bitcoin's price structure.
Disclaimer ⭕️
It is not financial advice, not an investment recommendation, and not affiliated with any financial institution, research firm, or organization of any kind. All content is provided for educational and informational purposes only. Always conduct your own research before making any financial decision. Indicator
Bitcoin Transaction Fees Z-Score | Astral Vision Bitcoin Transaction Fees Z-Score | Astral Vision 🌠💠
Transaction fees are one of the most direct expressions of genuine on-chain demand pressure. When users compete to get transactions confirmed, fees spike and historically those spikes have aligned tightly with late-stage cycle euphoria. Conversely, fee compression marks periods of network inactivity that have repeatedly preceded major accumulation opportunities.
This indicator standardizes total Bitcoin transaction fees (USD) in log space over a configurable lookback window, producing a Z-Score that exposes statistically extreme deviations from the long-term fee baseline, both to the upside and the downside.
Calculation ⚙️
`Z = (log(SMA(Total Fees USD, smooth)) − SMA(log_fees, length)) / StdDev(log_fees, length)`
Total on-chain fees in USD are first smoothed by a short SMA to reduce daily noise, then transformed into log space before standardization. The Z-Score measures how many standard deviations the current fee level sits above or below its long-term mean, compressing Bitcoin's exponential fee growth into a cycle-comparable signal.
Plots 📊
Z-Score line, colored by active regime (positive, negative, or neutral)
Extreme High threshold line (default 2.5)
Low threshold line (default −1.35)
Fill between Z-Score and Extreme High threshold when breached (distribution zone)
Fill between Z-Score and Low threshold when breached (accumulation zone)
Candle coloring on the price chart by active regime
Background highlight on the price chart when either threshold is active
Inputs 🎛️
`Z-Score Length (days)`: lookback window for mean and standard deviation calculation (default 730)
`Smooth Input (days)` : SMA applied to raw fee data before log transformation (default 7)
`Extreme High Threshold` : Z-Score level marking fee-driven distribution zones (default 2.5)
`Low Threshold` : Z-Score level marking fee-driven accumulation zones (default −1.35)
Colors 🎨
5 Astral Vision presets + custom override. Default: Futura. Positive color activates below the Low threshold; negative color activates above the Extreme High threshold; neutral applies between thresholds.
Purpose 🎯
Raw fee charts are dominated by Bitcoin's exponential price growth, making cycle-to-cycle comparison visually meaningless. Standard fee indicators plot absolute values with no statistical context, offering no signal on whether current fees are elevated or compressed relative to historical norms.
This indicator solves both problems: log transformation removes the exponential trend, and Z-Score standardization makes every cycle directly comparable regardless of Bitcoin's price magnitude. The result is a clean, threshold-driven signal that identifies when fee demand has reached statistically extreme levels, either as a distribution warning or an accumulation opportunity, directly overlaid on the price chart through candle and background coloring.
Disclaimer ⭕️
It is not financial advice, not an investment recommendation, and not affiliated with any financial institution, research firm, or organization of any kind. All content is provided for educational and informational purposes only. Always conduct your own research before making any financial decision. Indicator
Liquidity Sweep Engine [I.M]# Liquidity Sweep Engine
## Adaptive Ribbon · Smart Zones · Confidence Score
---
## OVERVIEW
The Liquidity Sweep Engine ("LSE ") is a discretionary-trading companion
that unifies four complementary market-structure components into a single
overlay: an **Adaptive Hull Ribbon**, a **BoS / CHoCH state machine**,
**Smart Zones** with a strength score, and a **Confidence Score panel**.
The screenshot below shows everything working together on BTCUSDT (Binance) on
the 30-minute timeframe — refer back to it throughout the description, since
each section refers to the same chart.
📊 **Live example chart:**
---
## WHAT YOU SEE ON THE CHART
Looking at the example image, from left to right and bottom to top:
- The **blue / purple ribbon** that snakes through the candles is the Adaptive
Hull Ribbon. Blue means slope-up (bullish momentum), purple means slope-down
(bearish momentum). The colour change marks where short-term momentum flips.
- Each **"BoS ▲"** or **"BoS ▼"** label at a dashed horizontal line is a
*Break of Structure* — the moment price closed past an unbroken swing high
(▲) or low (▼) **in the same direction as the existing trend**.
- Each **"CHoCH ▲"** or **"CHoCH ▼"** label is a *Change of Character* —
price broke a pivot **against** the current trend, flipping the trend state.
In the example, "CHoCH ▼" near the top is what told us the bullish leg was
ending; the BoS ▼ chain that follows is the new bearish trend confirming
itself.
- The **purple boxes extending to the right** are bearish Smart Zones (created
on bearish breaks). The **blue box** lower on the chart is a bullish Smart
Zone. Each zone is anchored to the origin candle of the move that produced
the break.
- The **EARLY** labels (small flash icons) print the first time price taps a
non-mitigated zone — a heads-up that an order-block area is being tested.
- The **panel in the bottom-right corner** is the Confidence Score: a 0–100
reading with a letter grade (D → A+), plus six rows showing the components
(Trend, Momentum, Volatility, Structure, Ribbon, active Zones).
The rest of the description explains how each of these pieces is computed.
---
## WHAT MAKES IT ORIGINAL
LSE is not a wrapper around `ta.pivothigh` / `ta.pivotlow`. The
originality is in how four independent ideas are combined and computed:
**Adaptive Hull Ribbon with slope acceleration**
The ribbon is a Hull Moving Average (HMA) plus its 2-bar-displaced sibling,
drawn as a filled band. A second-derivative reading (`slope1 − slope2`) detects
acceleration changes *before* the two lines cross, producing a "Pre-Bull" or
"Pre-Bear" state in the panel — a leading hint that complements the lagging
visual cross. In the example chart you can see this at the very top of the
move: the ribbon thins and rolls over before the actual colour flip occurs.
**Pivot-tracking BoS / CHoCH state machine**
Pivots are stored in a typed array and individually marked as broken when
price closes past them. The script then classifies each break as BoS or CHoCH
by comparing the break direction against the current trend state, instead of
just printing every pivot violation. This is why in the example you see only
**one** "CHoCH ▼" at the reversal followed by a chain of "BoS ▼" — the trend
flip is announced exactly once, then continuation breaks take over.
**Smart Zones with composite strength score**
When a structural break occurs, the engine looks back to find the last
opposite-coloured candle (the *origin candle*) and creates a zone there. Each
zone receives a 0–100 strength value computed from a 5-bar volume window
around the origin compared to a 20-bar volume average, plus a bullish/bearish
volume ratio. Zones below a user-defined minimum strength are skipped. As
price interacts with the zone, a touch counter is updated; once price closes
through the zone it is marked as **mitigated** and the box is faded rather
than deleted, so the chart keeps its historical context (you can see this in
the example: older zones still visible but visually softer than the active
one).
**Confidence Score**
A single 0–100 reading aggregates four sub-scores: trend strength
(|MHULL−SHULL|/ATR), momentum (RSI distance from 50 in the trend direction),
volatility regime (current ATR vs its 50-bar average) and structure freshness
(CHoCH = 20, BoS = 15, none = 0). Letter grades from D to A+ summarise the
overall environment.
To the author's knowledge no public PulseWire script combines these four
exact pieces with this specific scoring and zone-strength logic. Each
component on its own is a known idea; their joint computation and the way
they feed each other is what defines this script.
---
## HOW IT WORKS — STEP BY STEP
### 1. Pivot collection
The script collects pivots using the configurable lookback ("Pivot lookback",
default 10). Each pivot is stored as a typed object with bar index, price,
high/low flag and a *broken* flag.
### 2. BoS vs CHoCH classification
On each bar the script checks whether the close has moved past the most
recent unbroken pivot in the relevant direction. When it has:
- If the break direction matches the current trend state → **BoS**
(continuation).
- If the break direction reverses the current trend state → **CHoCH** (change
of character). The trend state is then flipped.
A dashed line is drawn from the broken pivot's bar to the current bar with
the corresponding label. **In the example image**, this is what produces the
horizontal dashed lines and the "BoS ▲ / BoS ▼ / CHoCH ▼" labels.
### 3. Smart Zone generation
On each structural break the script searches the prior 20 bars (configurable)
for the last candle of opposite colour to the move. That candle's high and
low form the top and bottom of the zone box. The zone is drawn extending to
the right and receives a strength score and a bullish-volume percentage.
Boxes use transparency that scales with strength (stronger zones look more
solid). **In the example image**, the two upper purple boxes were created on
the two CHoCH ▼ / BoS ▼ events near the top; the lower blue box was created
on the bullish BoS ▲ at the start of the move.
### 4. Zone lifecycle
- **Active**: visible while price has not closed through it.
- **Touched**: the touch counter increments each time price re-enters the
zone after leaving it (consecutive bars inside the zone count as a single
touch).
- **Mitigated**: when price closes past the far edge, the zone is faded and
stops extending. Mitigated zones remain on the chart by default for
historical reference; this can be disabled in the inputs.
- **Aged out**: zones older than the configurable maximum age are removed.
### 5. EARLY / CONFIRMED signals
- **EARLY** fires the first bar price enters a non-mitigated zone — an
anticipatory signal: better entry price, lower confirmation.
- **CONFIRMED** fires when the close reclaims the relevant zone edge after a
prior touch (close above the bottom for bull zones, close below the top for
bear zones) — a confirmation signal: worse entry price, higher
confirmation.
CONFIRMED has visual priority: when both fire on the same bar, only the
CONFIRMED label is shown.
### 6. Confidence Score
Each sub-score is computed every bar:
- **Trend strength (0–40):** `|MHULL − SHULL| / ATR`, scaled and capped.
- **Momentum (0–20):** RSI(14) distance from 50, in the direction of the
trend.
- **Volatility (0–20):** ATR(14) vs SMA of ATR(14, 50). Higher volatility
scores higher.
- **Structure (0–20):** 20 if a CHoCH just happened, 15 if a BoS, 0
otherwise.
The total is mapped to letter grades: A+ ≥ 85, A ≥ 70, B+ ≥ 55, B ≥ 40,
C ≥ 25, D below. **In the example image** the panel reads "Score: 15 D"
because the chart sits in a low-momentum recovery after a sustained
bearish leg — the panel correctly downgrades the environment despite the
local bullish bounce.
---
## HOW TO USE
LSE is designed as a **context tool**, not a black-box buy/sell system.
A suggested workflow:
1. **Read the panel first.** A high Confidence grade in the same direction as
the trend means the environment is aligned. A low grade is a caution flag.
2. **Use BoS / CHoCH labels to anchor bias.** A fresh CHoCH against your
open-position direction is the most common reason to reduce or exit.
3. **Treat Smart Zones as decision areas, not magic levels.** Touch counts
and strength values help pick which zones to watch; mitigated zones are
kept for reference but should not be traded as if they were still active.
4. **EARLY signals favour preparation, CONFIRMED signals favour execution.**
Aggressive traders may use EARLY with reduced size; more conservative
traders may wait for CONFIRMED. Both are filtered by the minimum-strength
input.
5. **Combine timeframes.** The script runs on any symbol and timeframe;
reading higher-timeframe structure alongside an execution timeframe is the
intended use.
The script does not place orders, does not include backtest results, and does
not claim a win rate. All decisions remain with the trader.
---
## INPUTS
**Detection**
- *Pivot lookback* — bars on each side required for a pivot. Higher = fewer,
more significant pivots.
- *Max pivots to track* — array cap to keep the script light.
**Structure (BoS / CHoCH)**
- *Show BoS / Show CHoCH* — toggle each event type.
- *Show broken pivot lines* — dashed line from broken pivot to current bar.
- *Show HH/HL/LH/LL* — optional swing labels.
**Adaptive Ribbon**
- *Ribbon base length* — HMA length (default 55).
- *ATR length / sensitivity* — internal volatility input for slope and
acceleration reading.
- *Band fill transparency, Glow, Line widths* — pure cosmetics.
**Smart Zones**
- *Trigger on* — BoS only / CHoCH only / both.
- *Min strength* — zones below this score are not drawn.
- *Origin candle lookback / Max age / Max count / Initial length* — geometry
and lifecycle controls.
- *Keep mitigated zones (faded)* — keep history vs auto-remove on mitigation.
- *Show mid-line / Show touch count* — optional decorations.
**Entry Signals**
- *Show entry signals / Min strength for signal* — gating.
- *Show EARLY signal* — toggle anticipation labels.
- *Show confidence label* — toggle the star/grade text on signals.
**Confidence Score Panel**
- *Show panel / Position* — visibility and corner.
**Alerts / Webhook**
- *Webhook event filter* — All / BoS only / CHoCH only / Retests only.
---
## ALERTS
When an alert is created with this indicator, the alert message contains a
JSON payload such as:
```
{
"symbol": "BTCUSDT",
"tf": "15",
"event": "BUY_CONFIRMED",
"price": 80000.0,
"trend": 1,
"score": 72,
"grade": "A",
"strength": 65,
"time": "1715000000000"
}
```
Possible `event` values: `BULLISH_BOS`, `BEARISH_BOS`, `BULLISH_CHOCH`,
`BEARISH_CHOCH`, `BUY_EARLY`, `SELL_EARLY`, `BUY_CONFIRMED`, `SELL_CONFIRMED`.
This format is intended for webhook consumers that need structured data
rather than free text.
---
## NOTES AND LIMITATIONS
- All structural logic is evaluated on bar close
(`alert.freq_once_per_bar_close`). Intra-bar values may differ from the
final, confirmed reading.
- The Hull moving average is naturally smoother than EMA/SMA but still lags;
the slope-acceleration reading is the script's attempt to compensate, not
eliminate, that lag.
- Volume-based zone strength depends on the symbol providing usable volume
data. On instruments without reliable volume, strength values will be less
informative.
- The Confidence Score is a heuristic aid, not a probability. Different
markets and timeframes will live in different score ranges, and that is
expected.
---
## DISCLAIMER
This script is published for educational and informational purposes only. It
is not financial advice and does not guarantee any particular outcome. Past
behaviour of the indicator on historical data does not imply future
performance. Trade at your own risk and size positions according to your own
risk management.
Indicator
CVDD Bands | Astral Vision CVDD Bands | Astral Vision 🌠💠
Coin Value Days Destroyed (CVDD) measures the aggregate economic weight of Bitcoin supply movements by combining the Realized Capitalization (the sum of all coins valued at their last on-chain movement price) with the cumulative destruction of coin-days through spending activity, smoothed over a 500-bar window and normalized against the fixed 21M supply ceiling. The result is a per-coin floor valuation that reflects how much long-term economic conviction the network has collectively expressed.
This indicator builds a three-band structure anchored to that baseline:
The mid band plots CVDD itself, historically coinciding with the deepest capitulation floors across every major Bitcoin cycle.
The bottom band shifts CVDD downward by a configurable factor, defining a sub-floor extreme that has marked generational buying opportunities.
The top band scales CVDD upward via a time-decaying power-law extension that compresses as Bitcoin matures, tracing the upper boundary of speculative excess against the network's fundamental valuation anchor.
Calculation ⚙️
`CVDD = (Realized Cap − 500-bar SMA of Total Transfer Volume) / 21,000,000`
The Realized Cap prices each coin at its last on-chain move; the smoothed transfer volume captures the cumulative economic weight of coin-day destruction. Dividing by the supply ceiling converts the result into a per-coin floor valuation.
`CVDD Bottom = CVDD × shift_factor`: a simple downward scalar applied to CVDD, defining the sub-floor capitulation extreme.
`CVDD Top = CVDD × 10^(a × time + b)`: a time-decaying power-law multiplier applied to CVDD. The exponent shrinks as Unix time increases, causing the top band to compress relative to CVDD as Bitcoin matures. Both the slope and intercept of the exponent are user-adjustable.
Plots 📊
- CVDD Mid band on the price chart with triple-layer glow (widths 8/4/2, transparency 60/30/0)
- CVDD Bottom band on the price chart with triple-layer glow
- CVDD Top band on the price chart with triple-layer glow in negative color
- Fill between Mid and Bottom bands
- Background highlight when price closes above the Top band (distribution warning)
- Background highlight when price closes below the Mid band (capitulation zone)
Inputs 🎛️
- `Top Extension Slope Factor (%)` scales the time-decay rate of the power-law top extension (default 100)
- `Top Extension Intercept Factor (%)` scales the vertical offset of the power-law top extension (default 100)
- `Bottom Shift (%)` scales CVDD downward to define the sub-floor extreme (default 120, interpreted as ×1.2 inversion)
Colors 🎨
5 Astral Vision presets + custom override. Default: Inferno. Positive color applies to Mid and Bottom bands; negative color applies to the Top band.
Purpose 🎯
Standard CVDD implementations plot a single line with no envelope, leaving traders without context for how far price is from both the accumulation floor and the distribution ceiling within the same framework.
This indicator converts CVDD into a full valuation band system: the bottom anchors the deepest possible accumulation zones, the mid marks the historical cycle floor, and the top provides a time-aware, power-law-adjusted resistance ceiling that self-compresses as Bitcoin's market matures.
The three-band structure lets you read where price sits within the full cycle valuation range at a glance, without any external oscillator.
Disclaimer ⭕️
It is not financial advice, not an investment recommendation, and not affiliated with any financial institution, research firm, or organization of any kind. All content is provided for educational and informational purposes only. Always conduct your own research before making any financial decision. Indicator
Indicator
RSI Pivot Break System + TP/SL█ OVERVIEW
RSI Pivot Break System + TP/SL is a technical tool that detects RSI-filtered price pivots, draws support and resistance levels, and generates breakout signals together with a complete trade setup – Stop Loss and three Take Profit levels based on Risk-Reward ratios.
The indicator combines classic pivot analysis with RSI momentum filtering. As a result, signals appear only when local highs or lows are confirmed by overbought or oversold market conditions.
Filtering pivots through RSI can also reduce the time needed to detect important pivots. Pivots forming inside Overbought/Oversold zones often represent the ending phase of local impulsive moves, which is why the default pivot length is set to a low value of 2.
After a breakout occurs, the indicator automatically creates a complete position visualization:
• entry level,
• Stop Loss,
• TP1 / TP2 / TP3,
• risk and reward zones.
█ CONCEPTS
The indicator was designed as a combination of price action, pivot analysis, and RSI momentum within a single breakout system.
Classic pivots often generate too many low-significance levels. Here, every pivot must additionally be confirmed by RSI:
• a pivot HIGH is created only when RSI is inside the overbought zone,
• a pivot LOW is created only when RSI is inside the oversold zone.
This allows the indicator to focus only on more significant local market extremes.
Pivot High and Pivot Low
Local price highs and lows detected using a specified number of candles on both sides.
• Pivot HIGH creates a potential resistance level
• Pivot LOW creates a potential support level
Once detected, the indicator automatically draws a horizontal level extended to the right.
RSI Filter
A pivot is accepted only when RSI meets a specific condition:
• for HIGH pivots → RSI ≥ overbought level
• for LOW pivots → RSI ≤ oversold level
This helps filter out many weak or random pivots.
The number of detected pivots can additionally be adjusted by modifying the Overbought/Oversold levels:
• adjusting Overbought/Oversold levels allows you to increase or decrease the number of detected pivots.
Breakout
A signal appears when a level is broken:
• breakout above resistance → BUY
• breakout below support → SELL
After the breakout, the level can either:
• remain on the chart,
or
• be automatically removed.
RSI Signal Filter
An optional additional filter can block signals during extreme RSI conditions:
• BUY signals can be blocked when RSI is too high
• SELL signals can be blocked when RSI is too low
This helps avoid entries after heavily extended moves.
TP/SL with Risk-Reward
After every signal, the indicator automatically calculates:
• entry level (close price of the breakout candle),
• Stop Loss,
• three Take Profit levels based on selected RR ratios.
SL can be calculated:
• using ATR × multiplier,
or
• as a percentage from the entry price.
█ FEATURES
1. Pivot Settings
• Pivot Length – number of candles required to confirm a pivot.
Lower values = more signals and faster pivot detection.
Higher values = stronger pivots but greater delay.
2. RSI Levels – Pivots
• RSI Overbought Level – minimum RSI level required for HIGH pivots
• RSI Oversold Level – maximum RSI level required for LOW pivots
This is the main pivot quality filter.
3. RSI Filters
Optional filter for blocking breakout signals:
• Enable signal blocking filter – enables the filter
• RSI Overbought (block BUY) – blocks BUY signals at very high RSI
• RSI Oversold (block SELL) – blocks SELL signals at very low RSI
4. Signal Settings
• Ability to select signal triangle size:
• Tiny
• Small
• Normal
5. Line Settings
• Delete broken lines after break – removes broken levels after breakout.
6. Colors
Full color customization for:
• HIGH levels,
• LOW levels,
• pivot price labels,
• BUY/SELL signals,
• line transparency.
Signal colors are also automatically synchronized with TP/SL levels and fill zones.
7. TP/SL Settings
• SL = ATR × or percentage from entry
• ATR Period
• ATR Multiplier
• SL %
• RR for TP1 / TP2 / TP3
Each TP can use its own RR multiplier.
8. TP/SL Display
Ability to individually enable:
• SL,
• TP1,
• TP2,
• TP3.
9. Position Visualization
The indicator automatically creates:
• entry line,
• SL line,
• TP lines,
• price labels,
• red risk zone,
• green reward zone.
When TP or SL is reached, all lines automatically stop extending.
█ APPLICATIONS
1. Local Structure Breakouts
The primary use of the indicator is trading breakouts of important local levels created by RSI-filtered pivots. A breakout may indicate a short-term market structure shift and the beginning of a new impulsive move in the breakout direction.
The best results usually occur when the breakout aligns with the dominant trend and is supported by increasing momentum. Before entering a position, it is worth additionally analyzing:
• the strength of the current move,
• higher timeframe trend direction,
• nearby support/resistance zones,
• available space for further price expansion.
2. Pivots as Important Market Levels
The pivots themselves can act as important reaction zones even without waiting for a breakout. Since the levels are additionally filtered by RSI, they often represent areas of local overbought or oversold market conditions.
Because of this, pivots can be used as:
• potential reaction zones,
• local support and resistance,
• profit-taking areas,
• price action and momentum observation zones.
In practice, the market often reacts to these levels multiple times before a final breakout occurs.
3. Position Management
Immediately after a signal appears, you can clearly see:
• defined risk level,
• potential RR,
• realistic targets,
• visual risk/reward relationship.
█ NOTES
• Small Pivot Length values generate more levels and more market noise.
• Large Pivot Length values create stronger levels but signals appear later.
• RSI is not used here as a classic entry oscillator, but as a pivot quality filter. Indicator
Indicator
Indicator
Sigma Channel [JOAT]JOAT Sigma Channel
Introduction
JOAT Sigma Channel is an open-source regression-based channel overlay built to identify the best-fit directional corridor across a search range of candidate windows.
It is designed to show whether price is traveling normally inside a fitted corridor, stretching away from it, reclaiming it, or moving into stress territory.
The problem it solves is model selection.
A fixed-length regression channel can look excellent in one regime and poor in the next.
If the market accelerates, slows down, or shifts its dominant drift horizon, a static window becomes less useful.
Sigma Channel solves that by searching a range of possible windows and selecting the strongest available fit.
That fit becomes the active corridor.
Around it the script builds multiple sigma tiers.
These tiers create a richer price-state map than a single upper and lower band.
The result is a more useful framework for reading acceptance, stretch, reclaim, and exhaustion.
Core Concepts
1. Multi-Window OLS Search
The script evaluates multiple candidate regression windows and scores them by fit quality.
for len = minWindow to maxWindow by stepWindow
= f_model(len)
2. Sigma-Tier Envelope Stack
The fitted centerline is surrounded by inner, core, outer, and stress layers.
3. Slope and Quality Diagnostics
The chosen model exposes both slope and fit quality.
4. Reclaim and Acceptance States
The script identifies when price reclaims or accepts back inside the corridor after extension.
5. Stress-State Shading
The most extreme statistical layer is visually emphasized.
6. Forward Projection
The active model projects forward to keep the corridor useful at the right edge.
7. Residual Awareness
Residual behavior helps judge whether the active model remains representative.
8. Gradient Candle Context
Bar coloring transitions with the current statistical state.
Features
Adaptive regression search: scans multiple windows instead of using one fixed length
Inner, core, outer, and stress bands: multiple sigma tiers for normal and abnormal travel
Slope-aware corridor logic: distinguishes positive and negative drift
Reclaim and acceptance events: return-to-channel behavior is identified
Stress shading: abnormal statistical extension is highlighted
Forward projection: the active corridor extends to the chart edge
Gradient candle tinting: bar color reflects the current z-state
Dashboard: slope, quality, window, and deviation state are summarized
Input Parameters
Model Search:
Minimum Window
Maximum Window
Window Step
Minimum R-Squared
Projection Bars
Deviation Envelope:
Inner Sigma
Core Sigma
Outer Sigma
Stress Sigma
Filter Stack / Visual System:
Bias EMA
ATR Length
Momentum RSI
Use EMA Bias Gate
Use RSI Gate
Use Volume Gate
Tint Bars
Show Projection
Show Dashboard
How to Use This Indicator
Step 1: Check the active slope and whether the corridor is upward, downward, or balanced.
Step 2: Check fit quality before trusting the active statistical path.
Step 3: Read whether price is inside the core corridor, at the outer layer, or in stress territory.
Step 4: Watch reclaims back into the channel after extension.
Step 5: Use the projection to organize the near-future chart space.
Indicator Limitations
The selected best-fit window can change as the market evolves
Linear regression becomes less representative in strongly nonlinear markets
Statistical extension does not guarantee immediate reversal
The indicator measures deviation from a model, not directional certainty
Originality Statement
This script is original in the way it combines adaptive regression selection, multi-tier sigma structure, reclaim logic, stress-state shading, and forward projection into one corridor framework.
The goal is not just to draw a regression channel.
The goal is to keep the active model responsive while preserving statistical context.
Disclaimer
This indicator is provided for educational and informational purposes only.
It is not financial advice.
Regression fit and statistical deviation do not predict future price with certainty.
Markets can remain extended or break away from the active fit entirely.
Best Use Cases
Reading whether price is behaving normally inside a fitted directional corridor
Identifying statistical stretch and stress states
Watching for reclaim behavior after extension
Combining statistical deviation with separate structure or liquidity analysis
Interpretation Notes
The channel should be trusted more when fit quality is stronger and the slope is clear.
Core travel is generally more normal than outer-band travel.
Stress states are especially useful when they coincide with separate structural or participation warnings.
The projection should be read as a continuation of the current best-fit model, not as a forecast guarantee.
Publication Notes
This script is intended to be published with a clean chart where the corridor, the active slope, and at least one reclaim or extension state are obvious.
The example chart should help the viewer understand how the band hierarchy works.
Avoid combining it with unrelated overlays in the publication image.
-Made with passion by jackofalltrades
Indicator
Indicator
Indicator
Liquidity Intelligence Entry SystemLiquidity Intelligence System
Liquidity Intelligence System is a liquidity-based market analysis framework designed around one central idea:
market movement is often shaped by liquidity pools, stop sweeps, directional bias, displacement, volatility conditions, and the quality of confluence around a signal.
This script is not designed to mark every candle, every swing, or every possible reversal. It is not intended to behave like a simple buy/sell indicator that reacts to one isolated condition. Its purpose is to detect structured liquidity events, compare multiple confluence models in the background, classify the current market regime, display signal quality, and project a visual risk/reward framework directly on the chart.
The script combines liquidity sweep detection, trend confirmation, FVG presence, volume expansion, RSI extremes, displacement behavior, market regime logic, adaptive preset modes, TP1/TP2/TP3 projection, visual liquidity mapping, and a model-performance dashboard into one organized workflow.
The goal is to help users review liquidity-based signals in a more structured way, not to promise future performance or replace independent analysis.
🔓 PUBLICATION NOTE
This script is published to provide a structured liquidity-analysis workflow.
The description is intentionally detailed because many users do not inspect every part of the Pine Script logic line by line. The purpose of this page is to explain what the script does, how its components connect, why the system is organized this way, and what limitations should be understood before using it.
The script should be treated as a decision-support and research tool. It is not financial advice, it is not an automated trading system, and it does not guarantee profitable results.
📌 OVERVIEW
At a high level, Liquidity Intelligence System does several things:
1. It detects liquidity sweep conditions around recent swing highs and swing lows.
2. It identifies buy-side liquidity and sell-side liquidity areas.
3. It can mark Equal High and Equal Low liquidity pools.
4. It changes swept liquidity levels visually once price takes them.
5. It evaluates 16 different liquidity/confluence signal models in the background.
6. It allows the user to manually choose which model should be active on the chart.
7. It prevents repeated same-direction signals from stacking unnecessarily.
8. It calculates virtual trade outcomes for each model.
9. It displays model statistics such as Trades, Win Rate, Profit Factor, Average R, and Net R.
10. It identifies the current best-performing model according to a selected metric.
11. It detects the current market regime using trend, ADX-style directional movement, ATR behavior, and candle body conditions.
12. It gives the most recent signal a Signal Quality score.
13. It displays a Signal Quality panel with a visual score bar.
14. It projects Entry, TP1, TP2, TP3, and SL levels on the chart.
15. It draws soft reward and risk zones around the active signal.
16. It provides theme modes for different chart styles.
17. It includes dynamic alert messages with signal, model, quality, regime, entry, TP, SL, and performance details.
The script is therefore not a single-purpose liquidity sweep marker. It is a multi-model liquidity intelligence and signal-review framework.
🧠 CORE IDEA
The core idea of the script is that a liquidity sweep by itself is only one part of the story.
A market may sweep a previous high or low, but that does not automatically mean the move is actionable. A sweep can lead to reversal, continuation, expansion, or false movement depending on the broader context.
For that reason, Liquidity Intelligence System does not rely on one condition alone.
Instead, it builds a layered model around the following question:
When liquidity is taken, what other evidence exists around that event?
The system can evaluate liquidity events together with:
- trend direction,
- recent FVG behavior,
- volume expansion,
- RSI extreme positioning,
- displacement strength,
- current market regime,
- and model-specific confluence.
This allows the script to compare different interpretations of the same market environment.
For example, one user may prefer simple liquidity sweeps, while another may prefer liquidity sweeps only when FVG and trend alignment are also present. The script does not force one fixed interpretation. It allows multiple models to run in the background while the user selects the model they want to display.
🧩 WHY THIS SCRIPT IS NOT A SIMPLE MASHUP
This script combines several concepts that are familiar in technical analysis and liquidity-based trading:
- swing highs and swing lows,
- liquidity sweeps,
- equal highs and equal lows,
- FVG-style imbalance logic,
- trend filters,
- volume filters,
- RSI conditions,
- displacement candles,
- ATR-based risk projection,
- dashboard statistics,
- alert messages.
These individual concepts are not unique by themselves.
The main purpose of this script is the way these elements are organized into one structured liquidity workflow:
Liquidity map
→ sweep detection
→ confluence model selection
→ market regime classification
→ signal quality scoring
→ TP1/TP2/TP3 projection
→ model-performance dashboard
→ dynamic alert system
Each part has a specific role.
- The liquidity map shows where price may be interacting with stop pools.
- The sweep engine defines the base signal event.
- The confluence models decide which extra filters should be required.
- The regime engine gives context about the current environment.
- The quality panel summarizes the last signal.
- The dashboard compares the performance of different models.
- The TP/SL projection gives a visual review structure.
- The alert system allows monitoring without constantly watching the chart.
For that reason, the script is intended as one complete liquidity-intelligence framework, not as a random collection of unrelated tools.
💧 WHAT THE SCRIPT DOES
The script begins by detecting swing-based liquidity references.
It uses recent pivot highs and pivot lows to define potential buy-side and sell-side liquidity levels.
Then it can classify and draw:
- BSL: Buy-Side Liquidity
- SSL: Sell-Side Liquidity
- EQH: Equal High liquidity
- EQL: Equal Low liquidity
When price later trades through one of these mapped levels, the script can visually mark that level as swept. This makes the liquidity map more informative because old untouched levels and swept levels are no longer displayed the same way.
After the liquidity engine identifies sweep conditions, the script evaluates whether the sweep qualifies under one of the available model combinations.
Those models are tested in the background, while the user chooses which one should be active on the chart.
The active model controls the visible LONG / SHORT labels and the projected Entry / TP / SL structure.
⚙️ HOW THE SCRIPT WORKS
1) LIQUIDITY SWEEP ENGINE
The script uses swing pivots to identify important recent highs and lows.
A buy-side sweep occurs when price moves above a previous swing high and then closes back below that swing high.
A sell-side sweep occurs when price moves below a previous swing low and then closes back above that swing low.
The script also checks sweep depth and wick rejection. This helps avoid treating every small break of a level as an equally meaningful sweep.
The sweep engine uses:
- swing pivot length,
- maximum sweep depth measured with ATR,
- rejection wick ratio,
- current candle structure,
- and the most recent mapped swing levels.
This base liquidity engine creates the foundation for all model combinations.
2) BSL / SSL LIQUIDITY MAP
The script can draw liquidity levels directly on the price chart.
The map may include:
- BSL above swing highs,
- SSL below swing lows,
- EQH when similar highs form near each other,
- EQL when similar lows form near each other.
The liquidity map is designed to be selective rather than excessive.
A quality mode controls how many levels are displayed:
- Balanced: more levels,
- Conservative: cleaner default view,
- Strict: fewer but more selective levels.
The script also limits the maximum number of active liquidity lines so the chart does not become overloaded.
3) SWEPT LIQUIDITY VISUAL STATE
When price reaches a mapped liquidity level, the script can mark that line as swept.
A swept liquidity line changes visually:
- the line becomes grey,
- the style changes,
- the label changes to SWEPT.
This makes it easier to distinguish active liquidity pools from liquidity that has already been taken.
This visual behavior is important because liquidity levels are not static forever. Once price has interacted with a level, its meaning may change.
4) EQUAL HIGH / EQUAL LOW LOGIC
The script can detect similar high or low points using an ATR-based tolerance.
Equal highs can represent a potential buy-side liquidity pool.
Equal lows can represent a potential sell-side liquidity pool.
Because instruments have different volatility, the tolerance is not fixed in raw price terms. It is scaled with ATR.
This makes the EQH / EQL logic more adaptive across different markets and timeframes.
🧠 16 MODEL SYSTEM
The script includes 16 model combinations.
These models are evaluated in the background:
1. LQ
2. LQ + Trend
3. LQ + FVG
4. LQ + Volume
5. LQ + RSI
6. LQ + Displacement
7. LQ + Trend + FVG
8. LQ + Trend + Volume
9. LQ + Trend + RSI
10. LQ + Trend + Displacement
11. LQ + FVG + Volume
12. LQ + FVG + RSI
13. LQ + FVG + Displacement
14. LQ + Volume + RSI
15. LQ + Trend + FVG + Volume
16. LQ + Trend + FVG + Volume + RSI + Displacement
The user can choose one active model from the settings.
The active model is the one that controls the visible chart signals.
The other models still run in the background for dashboard comparison.
This is one of the main ideas of the script: the user does not have to guess which confluence combination is currently performing better. The dashboard can compare the models over the visible historical calculation period.
📈 TREND COMPONENT
The trend component compares a fast EMA and a slow EMA.
If the fast EMA is above the slow EMA, the script treats the trend condition as bullish.
If the fast EMA is below the slow EMA, the script treats the trend condition as bearish.
This does not mean the EMA lines have to be plotted on the chart. They can work silently as internal filters.
When a model uses Trend, the liquidity signal must align with the EMA-based directional condition.
🟩 FVG COMPONENT
The FVG component checks for recent imbalance-style behavior.
The script identifies bullish and bearish FVG-style conditions and then checks whether such a condition has occurred within a recent lookback window.
This allows models such as:
- LQ + FVG,
- LQ + Trend + FVG,
- LQ + FVG + Volume,
- LQ + FVG + Displacement,
to require liquidity behavior together with recent imbalance context.
The FVG logic in this version is used as a filter and confluence component. It is not presented as a full FVG box-management system.
🔊 VOLUME COMPONENT
The volume component compares current volume against a volume moving average.
When current volume exceeds the selected volume average by the chosen multiplier, the script treats it as a volume expansion condition.
This can help models focus on sweeps that occur with stronger activity.
Volume is not used as proof of future direction. It is used as one additional context layer.
📉 RSI COMPONENT
The RSI component allows the script to include oscillator conditions in selected models.
For long models, RSI can be required to be near or below a selected lower threshold.
For short models, RSI can be required to be near or above a selected upper threshold.
This allows RSI to function as a contextual filter around liquidity events rather than as a standalone signal generator.
⚡ DISPLACEMENT COMPONENT
The displacement component checks whether the signal candle has enough body strength relative to ATR and total candle range.
A bullish displacement condition requires:
- bullish candle body,
- minimum body size relative to ATR,
- minimum body ratio inside the candle range.
A bearish displacement condition uses the opposite candle direction.
This helps identify signals where the sweep is followed by stronger directional candle behavior.
🧠 MARKET REGIME DETECTION
The script includes a market regime engine.
It classifies the current environment into states such as:
- Trend Up
- Trend Down
- Range
- Choppy
- High Vol
- Low Vol
- Neutral
The regime engine uses:
- directional movement logic,
- ADX-style trend strength,
- EMA trend direction,
- ATR compared to its average,
- candle body ratio behavior.
The purpose of this engine is to provide context.
A liquidity sweep in a trending market is not the same as a liquidity sweep in a range.
A signal during choppy conditions may require more caution than a signal during clean directional expansion.
The regime output is also used in the Signal Quality framework.
⭐ SIGNAL QUALITY SCORE
The Signal Quality score is a 0–100 style scoring framework.
The score is designed to summarize the most recent signal’s contextual quality.
It can consider:
- whether the signal is a valid liquidity event,
- whether the selected model’s trend condition is satisfied,
- whether the selected model’s FVG condition is satisfied,
- whether the selected model’s volume condition is satisfied,
- whether the selected model’s RSI condition is satisfied,
- whether the selected model’s displacement condition is satisfied,
- whether the market regime supports or conflicts with the signal direction.
The important detail is that the score is connected to the active model.
For example:
If the active model is LQ + FVG, FVG matters more directly.
If the active model is LQ + Volume, volume matters more directly.
If the active model is LQ + Trend + FVG + Volume, all of those conditions become part of the model-specific score.
This helps avoid a generic score that ignores the selected model’s logic.
📊 SIGNAL QUALITY PANEL
The Signal Quality panel displays a compact summary of the last signal.
It can show:
- current regime,
- market bias,
- last signal side,
- active model,
- signal score,
- mini score bar,
- alignment state.
The score bar is included to make the quality reading easier to review visually.
Example format:
Score: 78/100
Bar: ████████░░
This panel is not intended to guarantee that a signal will work. It simply summarizes how much contextual evidence was present when the signal appeared.
📊 MODEL DASHBOARD
The main dashboard compares the 16 models.
It includes:
- Trades
- WR
- PF
- Avg R
- Net R
- Active model row
- Best system row
The dashboard is meant for internal review.
It does not represent broker-executed trades. It is a virtual model-testing layer based on the script’s signal and TP/SL rules.
The dashboard helps the user compare whether one model is currently producing cleaner historical behavior than another, but it should not be interpreted as a guarantee that the same behavior will continue.
🏆 BEST SYSTEM ROW
The script can identify a Best System based on the selected metric.
The user can choose the best-system metric from:
- Net R
- Profit Factor
- Average R
- Win Rate
The system also uses a minimum trade count before a model can qualify for the Best row.
This is important because a model with only one or two trades can look misleading. The minimum trade threshold helps reduce the chance of highlighting a model with too little sample size.
🎛️ PRESET MODES
The script includes preset modes.
Available presets:
- Manual
- Scalping
- Intraday
- Swing
- Conservative
- Aggressive
- Funded Account Safe
The default preset is Intraday.
Preset modes do not simply change the name of the setting. They adjust internal effective values such as:
- TP / SL behavior,
- maximum bars in trade,
- sweep depth sensitivity,
- rejection requirement,
- FVG recency,
- volume multiplier,
- displacement requirements.
Manual mode allows the user to control the underlying settings directly.
Presets are included to make the script easier to adapt to different trading styles without requiring every setting to be adjusted one by one.
🎨 THEME SYSTEM
The script includes three visual themes:
Emerald Dark
A dark premium style using green and teal accents.
Crimson Pro
A more aggressive dark theme using red and high-contrast signal colors.
Ice Minimal
A cleaner light-style theme with black text and softer blue/grey visual structure.
The theme affects visual elements such as:
- dashboard colors,
- selected model row,
- best-system row,
- TP/SL/Entry line colors,
- TP/SL/Entry labels,
- reward and risk boxes.
The purpose is to make the same system usable across different chart backgrounds and visual preferences.
🎯 ACTIVE TRADE PROJECTION
When the active model produces a new signal, the script can project a visual trade framework.
The chart may display:
- Entry line
- TP1 line
- TP2 line
- TP3 line
- SL line
- reward zone
- risk zone
- price labels next to each level
The projected levels are based on risk multiples.
Default structure:
- TP1 = 1R
- TP2 = 2R
- TP3 = 3R
- SL = 1R risk
The user can adjust TP1, TP2, and TP3 R multiples from settings.
The projected structure is designed for review and visualization. It should not be treated as an instruction to enter a live trade without additional analysis and risk management.
🟢 TP / SL BACKTEST LOGIC
The script’s virtual testing engine is aligned with the TP1 / TP2 / TP3 structure.
If TP3 is reached, the virtual result is recorded using the selected TP3 R multiple.
If SL is reached, the result is recorded as -1R.
If the trade expires before TP3 or SL, the script can use the highest reached TP level or the open R result depending on what happened.
This creates a more consistent link between what appears visually on the chart and what the dashboard is evaluating.
Same-bar TP/SL behavior is handled by a conservative option. If both TP and SL appear to be hit during the same candle, the user can choose to count that situation conservatively.
🔁 NO CONSECUTIVE SAME-DIRECTION SIGNALS
The script includes a same-direction signal filter.
If a model produces a long signal, it will not keep printing long signals repeatedly until an opposite short signal occurs.
Likewise, if a model produces a short signal, it will not keep printing short signals repeatedly until an opposite long signal occurs.
This helps reduce repeated label clutter and makes the signal stream easier to review.
🚨 PRO ALERT SYSTEM
The script includes dynamic alert messages.
The alert message can include:
- signal side,
- active model,
- preset mode,
- quality score,
- market regime,
- alignment,
- entry price,
- TP1,
- TP2,
- TP3,
- SL,
- active model WR,
- active model PF,
- active model Avg R,
- active model Net R.
The script supports Text and JSON-style alert formats.
Important usage note:
To use the full dynamic Pro Alert message, create the PulseWire alert with:
Condition: Liquidity Intelligence System
Option: Any alert() function call
The regular alertcondition messages are fallback static alerts.
🧭 WHAT APPEARS ON THE CHART
Depending on settings, the script may display:
- LONG / SHORT labels,
- BSL liquidity lines,
- SSL liquidity lines,
- EQH liquidity lines,
- EQL liquidity lines,
- SWEPT liquidity labels,
- Entry line,
- TP1 line,
- TP2 line,
- TP3 line,
- SL line,
- reward area box,
- risk area box,
- price labels beside Entry / TP / SL,
- main model dashboard,
- Signal Quality dashboard.
This design is intentional.
The chart shows liquidity structure, active model signals, projected risk/reward, and review statistics in one organized view.
🧪 HOW TO USE THE SCRIPT
A practical workflow:
1. Add the script to your chart.
2. Start with the default Intraday preset.
3. Choose a theme that fits your chart background.
4. Select the active model you want to display.
5. Review the liquidity map: BSL, SSL, EQH, and EQL.
6. Wait for a liquidity sweep signal from the active model.
7. Check the Signal Quality panel.
8. Check the market regime and alignment state.
9. Review the Entry / TP1 / TP2 / TP3 / SL projection.
10. Compare the active model to the other models in the dashboard.
11. Use alerts if you want to monitor signals automatically.
12. Validate settings across the specific instruments and timeframes you actually trade.
The script is best used as a structured review framework, not as a blind execution system.
⚙️ SETTINGS REFERENCE
Manual Model Selection
- Active Signal Model: selects which of the 16 models appears on the chart.
- Preset Mode: selects the effective behavior profile.
- Show Active Model Labels: enables/disables signal labels.
- Signal Label Style: controls how much information appears in signal labels.
- LONG / SHORT Label Size: controls signal label size.
Virtual Trade Test
- ATR Length: ATR basis for risk calculations.
- Virtual TP ATR Multiplier: used in manual/preset logic where applicable.
- Virtual SL ATR Multiplier: used to define risk distance.
- TP1 R Multiple: first target multiple.
- TP2 R Multiple: second target multiple.
- TP3 R Multiple: third target multiple.
- Max Bars In Virtual Trade: maximum duration of virtual trade.
- If TP and SL Hit Same Candle, Count As Loss: conservative same-bar handling.
Liquidity Sweep
- Swing Pivot Length: pivot sensitivity.
- Max Sweep Depth ATR: maximum allowed sweep depth.
- Minimum Rejection Wick Ratio: wick rejection requirement.
- Show BSL / SSL Liquidity Lines: enables liquidity map.
- Show Equal High / Equal Low Lines: enables EQH/EQL.
- Liquidity Line Limit: maximum active liquidity lines.
- Liquidity Map Quality: controls how selective the liquidity map is.
- Equal High / Low Tolerance ATR: ATR-scaled equality tolerance.
Confirmation Filters
- Fast EMA Length: trend filter fast EMA.
- Slow EMA Length: trend filter slow EMA.
- EMA Source: source used for EMA calculations.
- Minimum FVG Size ATR: minimum FVG size filter.
- FVG Recent Bars: how recently FVG must have appeared.
- Volume SMA Length: volume baseline.
- Volume Spike Multiplier: volume expansion threshold.
- RSI Length: RSI calculation length.
- RSI Long Threshold: RSI condition for long models.
- RSI Short Threshold: RSI condition for short models.
- Minimum Displacement Body ATR: minimum displacement body size.
- Minimum Displacement Body Ratio: minimum body-to-range ratio.
Market Regime & Quality
- Show Signal Quality Table: enables/disables quality panel.
- Regime ADX Length: directional movement calculation length.
- Trend ADX Threshold: trend-strength threshold.
- Range ADX Threshold: range-condition threshold.
- Regime ATR Average Length: ATR baseline for volatility regime.
- High Volatility ATR Multiplier: high-volatility threshold.
- Low Volatility ATR Multiplier: low-volatility threshold.
- Choppy Body Ratio Threshold: body-ratio condition for choppy regimes.
Dashboard & Visuals
- Show Model Dashboard: enables/disables model comparison dashboard.
- Theme: selects Emerald Dark, Crimson Pro, or Ice Minimal.
- Dashboard Size: controls dashboard text size.
- BEST System Metric: selects best-system ranking logic.
- Minimum Trades For BEST Row: minimum sample size for best-system qualification.
Pro Alerts
- Enable Pro Alert Message: enables dynamic alert messages.
- Alert Message Format: selects Text or JSON-style format.
🧠 WHAT MAKES THIS SCRIPT ORIGINAL
This script uses familiar components such as swing highs/lows, EMA trend filters, volume comparison, RSI thresholds, ATR, and dashboard statistics.
Those components are not original by themselves.
The originality of this script lies in how those components are organized into a single liquidity-intelligence workflow:
Liquidity map
→ sweep detection
→ 16 model comparison
→ market regime classification
→ model-specific quality scoring
→ TP1/TP2/TP3 projection
→ dashboard review
→ dynamic alert output
This structure allows the script to function as a complete liquidity review environment rather than a simple signal marker.
⚠️ IMPORTANT PRACTICAL NOTES
The script’s behavior depends heavily on settings.
Signal frequency and signal quality may change based on:
- selected active model,
- preset mode,
- pivot length,
- sweep depth,
- rejection requirement,
- FVG recency,
- volume threshold,
- RSI thresholds,
- displacement settings,
- volatility conditions,
- symbol,
- timeframe.
A model that looks cleaner on one instrument may not behave the same way on another.
The dashboard is a virtual review layer. It is useful for comparing model behavior, but it should not be treated as proof of future results.
⚠️ LIMITATIONS AND SHORTCOMINGS
This script has important limitations:
- It does not guarantee profitable signals.
- It does not know future price movement.
- It does not replace risk management.
- It does not execute trades.
- It does not include broker slippage, commissions, spreads, or order-fill uncertainty.
- It uses chart data and bar-based logic.
- Same-bar TP/SL ambiguity is handled by a rule, not by true intrabar reconstruction.
- Liquidity sweeps can fail.
- FVG, trend, volume, RSI, and displacement filters can still produce false signals.
- The dashboard is historical and virtual, not a live brokerage performance report.
- Market regime classification is an analytical approximation, not an absolute truth.
- No confluence model removes all risk or uncertainty.
For these reasons, the script should be used as a structured analysis and review tool, not as a standalone trading system.
👤 WHO THIS SCRIPT MAY BE USEFUL FOR
This script may be useful for traders who:
- study liquidity sweeps,
- use smart-money-style market structure concepts,
- want BSL / SSL / EQH / EQL mapping,
- want multiple confluence models in one tool,
- want a visual TP1 / TP2 / TP3 framework,
- want a signal quality panel,
- want market regime context,
- want model comparison statistics,
- prefer organized chart-based review.
It may be less suitable for users who:
- want a fully automated trading system,
- want guaranteed buy/sell signals,
- do not use liquidity concepts,
- do not want dashboard-based review,
- prefer very minimal charts with no overlays,
- expect one model to work the same way on every market and timeframe.
🛡️ DISCLAIMER
This script is provided for educational and informational purposes only.
It does not constitute financial, investment, or trading advice.
No indicator can guarantee future results. Market conditions change, historical behavior does not ensure future behavior, and every user is responsible for their own analysis, validation, position sizing, and risk management.
Use this script as a structured decision-support and review framework, not as a promise of profitability.
Indicator
Indicator
Retracement Lattice [JOAT]JOAT Retracement Lattice
Introduction
JOAT Retracement Lattice is an open-source retracement and extension framework designed to turn a confirmed swing into a live working map.
It does more than place Fibonacci levels on a chart.
The script manages swing anchors, highlights the OTE pocket, overlays confirmed higher-timeframe retracement structure, shades premium and discount halves, and evaluates response quality inside the active pocket.
The problem it solves is inconsistency.
Manual retracement drawing is useful, but it can also become subjective very quickly.
Anchors are often moved emotionally.
Higher-timeframe confluence is ignored.
The midpoint is overlooked.
The response inside the retracement is treated as equivalent even when it is not.
Retracement Lattice standardizes the active swing and continuously updates the derived structure.
That creates a cleaner framework for pullback analysis, continuation planning, and location-based decision making.
Core Concepts
1. Confirmed Swing Anchor Engine
The lattice begins with a confirmed swing.
Pivot logic and anchor-state management determine which high and low form the active range.
pivotHigh = ta.pivothigh(high, pivotLen, pivotLen)
pivotLow = ta.pivotlow(low, pivotLen, pivotLen)
2. Full Retracement Stack
The script calculates a broad set of retracement and extension levels rather than only the most common ones.
fib236 = levelAt(0.236)
fib382 = levelAt(0.382)
fib500 = levelAt(0.500)
fib618 = levelAt(0.618)
fib705 = levelAt(0.705)
fib786 = levelAt(0.786)
3. OTE Pocket Emphasis
The 0.618 to 0.786 region is emphasized as the main response pocket.
4. Higher-Timeframe Confluence
A confirmed higher-timeframe lattice is projected alongside the local one.
5. Premium and Discount Shading
The upper and lower halves of the swing are shaded relative to the midpoint.
6. Extension Objectives
The active swing also provides continuation targets beyond the range.
7. Response Qualification
The script evaluates whether price is reacting constructively inside the active pocket.
8. Chart-Edge Guidance
Labels and projected guide objects keep the live map readable near the right edge of the chart.
Features
Confirmed anchor-state engine: stable swing selection using pivot confirmation
Expanded retracement stack: 0.236, 0.382, 0.500, 0.618, 0.705, and 0.786
OTE pocket emphasis: the main response zone is highlighted
Extension objectives: continuation levels project beyond the swing
Higher-timeframe confluence: confirmed HTF lattice is shown
Premium / discount shading: auction halves are visible at a glance
Response qualification: pocket interaction is graded instead of assumed
Object-managed edge labels: the current range stays readable
Dashboard: anchor direction, confluence, and pocket state are summarized
Input Parameters
Swing Anchor:
Swing Lookback
Pivot Length
Reverse Orientation
Volume-Validated Pivots
Volume Baseline
Volume Threshold
Higher Timeframe / Display:
Show Higher Timeframe Grid
Higher Timeframe
Show Classic Retracements
Show Minor Levels
Show OTE Band
Show Extensions
Show Dashboard
Confluence Tolerance
Shade Auction
How to Use This Indicator
Step 1: Identify the active swing anchor pair.
Step 2: Check whether price is trading in premium or discount relative to the midpoint.
Step 3: Focus on the OTE pocket when the broader structure supports it.
Step 4: Compare the local lattice to the confirmed higher-timeframe lattice.
Step 5: Use the extensions to organize continuation targets after response.
Indicator Limitations
Anchors settle only after pivot confirmation, which is intentional non-repainting behavior
Strong trends can continue without deep retracement into the pocket
Confluence improves context but does not force a reaction
Retracement tools provide structure, not certainty
Originality Statement
This script is original in how it turns a retracement tool into an active framework with anchor-state management, OTE response logic, premium-discount shading, higher-timeframe confluence, and extension objectives.
The components are unified around one job:
to make pullback location more structured and less subjective.
Disclaimer
This indicator is provided for educational and informational purposes only.
It is not financial advice.
Retracement and extension levels are analytical references and do not guarantee support, resistance, or target completion.
Use risk management and independent judgment at all times.
Best Use Cases
Structuring pullback analysis after a confirmed directional swing
Comparing local retracement behavior to confirmed higher-timeframe levels
Locating the OTE pocket inside a stable swing map
Planning continuation targets with extension levels
Interpretation Notes
The midpoint is important because it quickly reveals whether price is trading in the premium or discount half of the current auction.
The OTE pocket is most useful when the broader structural narrative already supports the same directional idea.
Higher-timeframe confluence should be treated as context improvement, not as a guarantee that the level must react.
Publication Notes
This script is intended to be published with a clean chart showing the active anchor, the highlighted OTE pocket, and the higher-timeframe overlap when it exists.
The chart example should make the active swing easy to understand.
Avoid clutter from unrelated studies or excessive drawings.
-Made with passion by jackofalltrades
Indicator
Indicator
Indicator
Ultimate Volume Warfare [CLEVER]Overview
Ultimate Volume Warfare is a comprehensive volume-analysis system built to study how market participation interacts with price structure, volatility, and momentum conditions across different trading environments. The indicator combines multiple layers of volume behavior into a unified analytical framework designed to help traders observe shifts in market activity with greater clarity and structure.
At its foundation, the script focuses on the relationship between price movement and trading participation rather than treating raw volume as an isolated metric. By combining pivot-based divergence analysis, adaptive volume calculations, relative volume behavior, and contextual filtering systems, the indicator attempts to highlight moments where participation characteristics begin changing beneath price action.
The system includes an advanced volume classification model inspired by participation-based market behavior. Different conditions such as climax activity, exhaustion phases, accumulation behavior, distribution pressure, absorption zones, and abnormal spike events are visually separated using dedicated color logic. This structure is designed to make changes in participation strength easier to identify during trending, ranging, and volatile market conditions.
A major component of the framework is its divergence engine, which compares confirmed swing structures in price against confirmed swing structures in volume. The script supports both regular and hidden divergence detection using pivot-based confirmation logic. Because the system relies on completed pivot structures, signals naturally appear after confirmation instead of attempting to predict unfinished market swings in real time. This confirmation-based approach is intended to reduce unstable signal behavior while preserving structural consistency.
To improve adaptability across different market conditions, the indicator uses volatility-sensitive calculations that dynamically adjust internal thresholds according to changing ATR behavior. This allows the script to react differently during low-volatility consolidation phases versus high-volatility expansion phases, helping the analytical logic remain more responsive across multiple instruments and timeframes.
The indicator also integrates relative volume analysis and spike-detection systems to identify periods where market participation exceeds normal historical behavior. Heatmap zones, spike markers, and confluence conditions are used to visually emphasize moments of unusually strong activity that may represent heightened institutional participation, aggressive momentum expansion, or temporary liquidity imbalance.
In addition to standalone volume analysis, the script supports optional confirmation filters including EMA trend alignment, ATR expansion conditions, higher timeframe participation analysis, and relative volume filtering. These layers are designed to provide broader contextual alignment before signals become visible, helping reduce weaker market conditions where participation structure may lack consistency.
The higher timeframe module introduces an additional contextual layer by comparing current higher timeframe participation against its own historical average behavior. This helps users observe whether broader participation conditions are expanding or contracting while operating on lower execution timeframes. The script uses non-lookahead calculations to reduce misleading historical behavior as much as possible within Pine Script limitations.
The interface is designed as a full analytical environment rather than a minimal signal generator. Divergence structures, classification coloring, spike visualization, confirmation ribbons, confluence markers, RVOL heatmaps, and statistical dashboards all work together to provide layered insight into changing participation behavior across the chart.
Ultimate Volume Warfare is intended for educational and analytical chart-study purposes only. The script does not predict future market direction or guarantee trading performance. All signals and classifications should be interpreted within broader market context, liquidity conditions, volatility structure, and individual risk management practices.
Core Concept
The core concept behind Ultimate Volume Warfare is the idea that market participation often provides additional context beyond price movement alone. Instead of treating volume as a simple confirmation tool, the script approaches volume as a dynamic behavioral component that can be analyzed alongside volatility, structure, momentum, and multi-timeframe conditions to study how market activity evolves during different phases of price action.
The framework is built around the relationship between price swings and participation strength. The script continuously evaluates whether volume behavior is supporting, weakening, accelerating, or diverging from underlying price movement. By comparing confirmed pivot structures in both price and volume, the system attempts to identify areas where participation characteristics begin changing relative to market structure. This divergence-based methodology is designed to study the interaction between directional movement and participation intensity rather than attempting to forecast exact future outcomes.
A major part of the system focuses on contextual volume interpretation. Instead of using a single static threshold, the indicator separates participation into multiple behavioral categories such as climax activity, exhaustion behavior, absorption conditions, accumulation pressure, distribution pressure, and abnormal spike events. Each classification attempts to represent a different form of participation environment occurring inside the market. The objective is not to label market direction with certainty, but to help visualize how trading activity changes during expansion, compression, continuation, or reaction phases.
The script also emphasizes adaptive behavior rather than rigid calculations. Market volatility changes constantly across assets and timeframes, so the indicator uses ATR-sensitive normalization logic to dynamically adjust several internal thresholds. This allows participation conditions to scale differently during high-volatility expansion phases compared to quieter consolidation environments. By adapting to changing volatility structures, the system attempts to maintain analytical consistency across multiple market conditions.
Another foundational concept within the framework is confluence analysis. Instead of relying on a single event to generate chart signals, the indicator can combine multiple contextual layers such as divergence confirmation, relative volume expansion, higher timeframe participation state, volatility filters, EMA alignment, and spike activity. The goal of this layered structure is to provide broader analytical context around participation behavior rather than reducing market analysis to isolated signals.
The indicator also incorporates relative volume analysis to compare current activity against historical participation averages. This helps highlight areas where current market engagement exceeds normal conditions, which may indicate periods of stronger liquidity, increased attention, or temporary participation imbalance. Heatmap zones, spike markers, and confluence visuals are designed to make these changes easier to identify visually during active market conditions.
Higher timeframe participation analysis adds another contextual dimension to the system. By comparing higher timeframe volume against its own average conditions, the framework attempts to provide additional insight into whether broader market participation is expanding or declining while traders operate on lower execution timeframes. This multi-timeframe structure is intended to improve contextual awareness without relying solely on local chart activity.
The overall design philosophy of Ultimate Volume Warfare is centered around structured market observation rather than predictive certainty. The script is designed to organize complex participation behavior into a visual analytical environment where users can study the interaction between volume, volatility, and structure through multiple synchronized layers of confirmation and contextual filtering.
Because the system relies on confirmed pivot structures and historical participation calculations, certain signals may naturally appear after structural confirmation has occurred. This behavior is part of the confirmation-based methodology used throughout the framework and helps reduce unstable live-candle behavior that can occur when analyzing unfinished market structures.
Key Features — Ultimate Volume Warfare
Advanced Volume Classification Engine
The indicator uses a layered volume analysis system designed to separate normal market participation from abnormal activity. Instead of displaying raw volume alone, the script classifies volume behavior into multiple conditions such as Climax Volume, Exhaustion, Accumulation, Distribution, Absorption, and Spike Events. This allows traders to visually identify changing market participation and potential momentum transitions with greater clarity. The classification system dynamically adapts to volatility conditions, helping the indicator remain responsive across different assets and market environments.
Adaptive Volume Moving Average System
A customizable volume moving average is integrated to help smooth market activity and identify shifts in participation strength. Users can choose between a traditional SMA-based approach or an adaptive ALMA smoothing method for more responsive volume tracking. This adaptive behavior helps reduce unnecessary noise while still reacting efficiently during periods of increased market activity.
Volume Divergence Detection
The script includes a pivot-based divergence engine that compares price structure against volume structure. By monitoring the relationship between swing highs/lows and underlying participation strength, the indicator highlights both regular and hidden divergence conditions. These divergence signals are confirmation-oriented and rely on completed pivot structures, which helps reduce impulsive or premature signaling behavior.
Multi-Layer Signal Filtering
To improve signal quality, the indicator supports several optional filters including EMA trend filtering, ATR-based volatility filtering, volume threshold filtering, and higher timeframe confirmation logic. These filters allow users to align signals with broader market conditions rather than relying solely on isolated volume behavior. The layered filtering approach is designed to support structured analysis workflows across multiple trading styles.
Higher Timeframe Volume Analysis
The integrated MTF (Multi-Timeframe) system evaluates higher timeframe volume conditions alongside the active chart timeframe. This helps traders observe whether participation is expanding or declining on broader market structures. By combining local chart activity with higher timeframe volume context, the indicator attempts to provide a more balanced interpretation of market participation.
Relative Volume Heatmap Zones
The indicator contains an optional RVOL heatmap system that visually highlights periods where relative volume exceeds predefined thresholds. These zones help identify areas of increased participation, heightened volatility, or potential institutional activity. The heatmap acts as an additional contextual layer rather than a standalone trading trigger.
High Confluence Signal Detection
A specialized confluence system combines divergence conditions with advanced volume classifications such as spikes, absorption, and climax activity. When multiple internal conditions align simultaneously, the script highlights stronger confluence zones for additional visual awareness. This feature is intended to assist with market structure observation rather than guarantee directional outcomes.
Dynamic Visual Structure
The script includes extensive visual customization including adaptive colors, divergence lines, spike markers, chart overlays, confirmation ribbons, signal labels, and statistical tables. The design focuses on improving readability while allowing users to personalize the visual experience according to their workflow and charting preferences.
Real-Time Statistical Monitoring
Built-in statistical tables provide ongoing tracking of daily and weekly signal activity, volume distribution, relative volume values, and higher timeframe participation states. These panels are designed to help users monitor evolving market behavior directly from the chart without requiring separate tools or calculations.
Confirmation-Based Logic Design
The overall architecture prioritizes confirmation-oriented behavior rather than predictive forecasting. Many components rely on completed pivot structures, confirmed candle states, and finalized volume conditions before generating visual outputs. Because of this structure, some delay may naturally occur in signal plotting, particularly during divergence analysis. This behavior is expected and reflects the script’s emphasis on structural confirmation instead of instant projection.
How It Works — Ultimate Volume Warfare
The indicator works as a multi-layer volume intelligence system that combines raw volume, price structure, volatility, and higher-timeframe context into a single analytical framework. Instead of treating volume as a simple histogram, it reconstructs market behavior by classifying participation, detecting structural shifts, and validating signals through confirmations.
1. Volume Foundation Layer
At the core, the script continuously reads raw market volume and compares it against a 50-period average volume baseline. From this it calculates relative volume (RVOL), which becomes the foundation for most logic decisions. This step helps the system understand whether current activity is normal, elevated, or extreme compared to recent history.
2. Adaptive Volatility Normalization
Market conditions are not fixed, so the indicator adjusts sensitivity using ATR-based volatility scaling. When volatility expands, thresholds become more relaxed; when volatility contracts, thresholds become tighter. This prevents false signals during erratic or quiet market phases and keeps behavior consistent across different market regimes.
3. Volume Behavior Classification Engine
Each candle’s volume is categorized into behavioral states rather than just numbers:
Climax → Extremely high participation (possible exhaustion zones)
Absorption → High volume but limited price movement (smart money activity)
Exhaustion → Weak follow-through after heavy participation
Accumulation / Distribution → Directional pressure with controlled flow
Spike Events → Sudden abnormal participation bursts
This layer transforms raw volume into market intent interpretation.
4. Structure-Based Divergence System
The indicator uses pivot-based swing detection (confirmed highs and lows) to compare:
Price swings (structure)
Volume swings (participation)
If price makes a new extreme but volume fails to confirm (or reverses behavior), it generates:
Regular Divergence (trend weakening signals)
Hidden Divergence (continuation signals)
Because pivots require confirmation, signals appear only after structure completes, reducing noise but introducing slight delay.
5. Multi-Factor Filtering System
Before any signal becomes valid, it passes through multiple optional filters:
EMA Trend Filter → ensures signals align with overall trend
ATR Filter → ensures sufficient volatility for valid movement
Volume Filter → avoids low participation environments
Wick Logic (Accurate Mode) → confirms rejection behavior
HTF Filter → validates higher timeframe volume direction
This creates a confluence-based confirmation model, not a single-trigger system.
6. Signal Confirmation Engine
After divergence detection, signals are not immediately printed. They are validated through:
Volume classification (spike / absorption / climax alignment)
Filter alignment (trend + volatility + structure agreement)
Multi-timeframe confirmation (optional)
Only when multiple conditions agree, the system produces Buy/Sell labels and confluence stars.
7. Higher Timeframe Context Layer
The script optionally pulls volume data from a higher timeframe (like Daily). It compares:
Current volume trend (expanding or declining)
Higher timeframe volume state
This ensures signals are not isolated to a single timeframe and helps detect broader institutional participation shifts.
8. Visual Intelligence Layer
All internal logic is translated into:
Colored volume bars (based on classification)
Spike markers on chart and pane
Divergence lines between pivots
Confluence stars for strong setups
Heatmap zones for RVOL spikes
Stats table for session tracking
This layer turns complex logic into readable visual structure.
9. Confirmation-Based Philosophy
The entire system is built on one principle:
Nothing is predicted — everything is confirmed after structure completes.
Because of pivot confirmation and multi-condition validation, signals may appear slightly delayed, but they are structurally more reliable than real-time guessing systems.
Final Idea
In simple terms, this indicator works like a market behavior decoder:
It doesn’t just show volume — it interprets who is active, how strong they are, whether they are absorbing or pushing price, and whether the trend is supported or weakening, then confirms it using structure + filters + multi-timeframe agreement.
How It Works — Deep Core Logic (House Rules Safe)
This script is basically a volume-based market behavior engine that converts raw volume + price movement into structured trading intelligence. Instead of using simple indicators, it builds a full system that reads participation, pressure, and structural confirmation together.
1. Raw Data Foundation Layer
The system starts by continuously reading:
Volume (market participation)
Price (open, high, low, close)
Range behavior (high–low movement)
ATR (volatility baseline)
From this, it builds a foundation of how active the market is and how far price is moving for that activity.
2. Relative Volume Intelligence (RVOL Core)
It calculates:
Average volume (baseline)
Relative volume (current vs average)
This allows the system to classify whether the market is:
Normal activity
High participation
Unusual/institutional level activity
RVOL becomes the main pressure meter of the script.
3. Adaptive Volatility Control System
Instead of using fixed thresholds, the script adjusts sensitivity using volatility:
High volatility → loosens strictness
Low volatility → tightens strictness
This ensures the indicator does not overreact in choppy markets or underreact in fast trends.
This is what makes the system adaptive instead of static.
4. Volume Behavior Classification Engine
Each candle is analyzed and categorized into behavioral types:
Climax → Extreme activity, possible reversal pressure
Absorption → High volume but controlled price movement (hidden buying/selling)
Exhaustion → Weak follow-through after heavy activity
Accumulation → Quiet buying under pressure
Distribution → Quiet selling under strength
Spike Events → Sudden aggressive participation bursts
This converts raw volume into market intention mapping.
5. Pivot-Based Structure Detection
The system uses pivot logic (confirmed swing highs/lows):
Detects structural market points
Builds swing relationships
Waits for confirmation (not live guessing)
This is important because it ensures signals only appear when structure is completed, not during formation.
6. Volume vs Price Divergence System
This is one of the core engines:
It compares:
Price direction (higher highs / lower lows)
Volume behavior at those points
It detects:
Regular Divergence → trend weakening
Hidden Divergence → continuation strength
If price and volume disagree → it signals imbalance.
7. Multi-Factor Signal Filtering
Before any signal is allowed, it must pass filters:
EMA trend direction (trend alignment)
ATR movement strength (volatility validation)
Volume confirmation filter (participation check)
Wick rejection logic (price rejection strength)
Optional higher timeframe filter (market context)
This creates a confluence gate system.
If conditions don’t align → no signal.
8. Confluence Engine (Final Signal Decision Layer)
After divergence + classification + filters:
The system checks for alignment like:
Spike + divergence
Absorption + reversal structure
Climax + weak follow-through
When multiple conditions agree → it produces:
Buy / Sell labels
Confluence star signals
This is the final decision layer of the system.
9. Higher Timeframe Confirmation Layer (MTF Logic)
It optionally pulls higher timeframe volume:
Checks if volume is expanding or declining on higher TF
Aligns lower TF signals with broader trend context
This helps reduce false signals against the bigger trend.
10. Visual Interpretation Layer
Everything is converted into visual structure:
Colored volume bars (behavior-based)
Spike markers (sudden activity)
Divergence lines (structure mismatch)
Signal labels (buy/sell)
Confluence stars (strong setups)
Stats table (market session tracking)
This makes complex logic readable on chart.
Final Working Principle
At its core, the system works like this:
It does not predict price. It studies how volume behaves relative to structure, confirms conditions across multiple filters, and only then highlights high-probability market pressure zones.
Settings & Customization — Ultimate Volume Warfare
This script is built like a modular trading system, meaning every major component can be tuned depending on your trading style (scalping, intraday, swing). The settings are designed to control signal speed, accuracy, sensitivity, and visual clarity.
1. Signal Sensitivity Control (Core Behavior)
Signal Intensity (sigMode)
Accurate
Strict confirmation rules
Strong filters (wick + structure quality)
Fewer signals, higher reliability
Balanced (Default)
Middle ground between speed and accuracy
Best for most traders
Aggressive
Fast signals, early entries
More noise but earlier detection
👉 This is the main brain setting of the system.
divPivot (Structure Depth)
Controlled automatically by sigMode:
Accurate → deeper pivots (5)
Balanced → medium (3)
Aggressive → shallow (2)
👉 Higher pivot = more stable but slower signals
👉 Lower pivot = faster but noisier signals
2. Volume Behavior Customization
Volume Moving Average (maLength)
Controls smoothing of volume trend
Lower value → fast reaction (scalping)
Higher value → stable trend view (swing)
ALMA Toggle (useALMA)
ON → smoother, adaptive volume curve
OFF → standard SMA (simpler structure)
Volume Spike Multiplier (spikeMult)
Defines what is considered “abnormal volume”
Low value → more spike signals
High value → only extreme spikes
👉 Recommended:
Crypto → 2.0–2.5
Forex → 2.5–3.5
Stocks → 2.0–3.0
3. Volume Classification Control
These settings control how market behavior is labeled:
Climax Volume sensitivity
Absorption detection strength
Exhaustion filtering
Accumulation / Distribution recognition
👉 You don’t manually change thresholds here; instead, they react automatically using:
Average Volume (50 SMA)
Dynamic Volatility Multiplier (dynMult)
✔ This makes the system self-adjusting across market conditions
4. Trend & Filter System (Signal Protection Layer)
EMA Filter (useEmaFilter)
ON → trades only in trend direction
OFF → allows counter-trend signals
EMA Length (emaLen)
200 = strong trend filter (safe mode)
50–100 = faster trend detection
ATR Filter (useAtrFilter)
Ensures real market movement exists
Prevents signals in low volatility zones
ATR Multiplier (atrMult)
Low → more signals (sensitive)
High → stricter entry conditions
Volume Filter (useVolFilter)
Blocks weak participation signals
Helps avoid fake breakouts
5. Higher Timeframe Control (MTF Layer)
HTF Filter (useHTFFilter)
ON → only trade with higher timeframe volume direction
OFF → independent signals
HTF Resolution (htfRes)
D (Daily) → swing confirmation
4H → intraday trend filter
1H → scalping context
👉 This is your big picture alignment tool
6. Visual Customization (Chart Control Layer)
Volume Colors
Up Volume / Down Volume / Neutral
Custom spike colors
Classification colors (climax, absorption, etc.)
👉 Used for quick visual reading of market behavior
Spike Display Settings
Show spikes on volume pane
Show spikes on main chart
Show icon markers (diamond)
👉 Helps detect sudden institutional activity
Heatmap (RVOL Zones)
ON → highlights high activity zones
Sensitivity (rvolSens):
Lower = more zones
Higher = only extreme activity zones
7. Divergence System Control
showDiv
Enables/disables full divergence engine
Strength of Divergence Logic:
Based on pivot structure
Compares price swings vs volume swings
You can tune behavior indirectly via:
sigMode (accuracy vs speed)
divPivot (structure depth)
8. Signal Display Control
showSignals
Controls:
Buy/Sell labels
Entry markers
Visual Options:
Chart overlay signals
Pane signals
Confirmation stars (confluence)
👉 Helps switch between:
Clean chart mode
Full analysis mode
9. Statistics & Table System
showTable
Displays:
Daily buy/sell activity
Weekly trend bias
RVOL strength
MTF volume state
👉 Useful for:
Session monitoring
Market behavior tracking
Strategy validation
10. Recommended Presets (Practical Use)
🔹 Scalping Setup
Aggressive mode
Low divPivot
EMA filter OFF
HTF OFF
Spike sensitivity low
🔹 Intraday Setup (Best Balanced)
Balanced mode
EMA filter ON (100–200)
ATR filter ON
HTF (4H or D)
🔹 Swing Trading Setup
Accurate mode
EMA 200 ON
HTF Daily ON
Higher spike threshold
Strict ATR filter
Final Idea
This system is not a fixed indicator — it is a customizable volume intelligence framework.
You control:
Speed (Aggressive → Accurate)
Safety (filters)
Trend alignment (EMA + HTF)
Sensitivity (spikes + pivots)
Visual depth (signals + heatmap)
👉 In simple terms:
You are not just using an indicator — you are tuning a market behavior engine according to your strategy.
Mashup Rules & Combined System Logic — Deep Explanation (House Rules Safe)
This script is not a single indicator — it is a mashup system, meaning multiple independent trading models are merged into one unified decision engine. Each module works separately, but final signals only appear when multiple layers agree.
Think of it like a multi-department trading desk where every department must approve before a signal is released.
1. Core Mashup Structure (System Architecture)
The system is built from 5 main modules:
1. Volume Intelligence Module
Classifies raw volume into behavior types:
Climax
Absorption
Exhaustion
Accumulation / Distribution
Spikes
👉 This tells what kind of pressure is in the market
2. Price Structure Module (Pivot Engine)
Detects swing highs and swing lows
Builds market structure using confirmed pivots
Identifies:
Regular divergence
Hidden divergence
👉 This tells where the market structure is changing
3. Trend Filter Module (EMA System)
Checks overall market direction using EMA
Controls whether trades align with trend or against it
👉 This tells which side is dominant
4. Volatility Filter Module (ATR System)
Measures market movement strength
Blocks low-quality or weak movement conditions
👉 This tells whether market is active enough for signals
5. Multi-Timeframe Module (HTF Logic)
Reads higher timeframe volume trend
Confirms whether lower timeframe signals match bigger structure
👉 This tells whether the move is supported by broader market flow
2. Mashup Rule System (How Everything Combines)
The system follows a strict rule chain:
STEP 1 — Detection Phase
Each module generates raw conditions:
Volume detects pressure
Price detects structure shift
Trend detects direction
Volatility detects strength
HTF detects macro alignment
STEP 2 — Filtering Phase
All signals must pass filters:
EMA alignment check
ATR movement validation
Volume participation check
Wick rejection logic (optional strict mode)
HTF confirmation (if enabled)
👉 If even one major filter fails → signal is blocked
STEP 3 — Confluence Phase (Mashup Core)
This is where systems merge.
A valid signal requires at least 2–3 conditions aligning, such as:
Divergence + Spike
Absorption + Trend alignment
Climax + Weak continuation
Structure break + Volume surge
👉 This is the decision-making engine
STEP 4 — Confirmation Phase
Even after confluence:
Signal waits for candle confirmation
Pivot must be fully formed
No mid-candle prediction allowed
👉 This ensures no premature signals
3. Combined Logic (How Mashup Actually Works)
Final decision is based on:
BUY Logic Example:
Bullish divergence detected
AND
Volume shows absorption or spike
AND
Price is above EMA trend
AND
ATR confirms movement strength
AND
HTF is not bearish
✔ THEN → Buy signal appears
SELL Logic Example:
Bearish divergence detected
AND
Volume shows distribution or spike
AND
Price is below EMA trend
AND
Volatility is sufficient
AND
HTF is not bullish
✔ THEN → Sell signal appears
4. Conflict Handling System
If modules disagree:
Volume says bullish but structure says bearish → no trade
Trend bullish but divergence bearish → wait mode
HTF opposite direction → signal weakened or blocked
👉 This prevents random or emotional signals
5. Strength Levels (Confluence Ranking)
Signals are not equal:
Weak Signal
Only divergence OR only volume spike
Medium Signal
Divergence + trend alignment
Strong Signal
Divergence + spike + absorption/climax
High Confluence Signal ⭐
Multiple modules agree simultaneously
Marked with special star confirmation
6. Why This Mashup System is Powerful
Because it does NOT rely on one idea.
It combines:
Volume behavior (who is active)
Price structure (what is happening)
Trend direction (who is in control)
Volatility state (is market ready)
Higher timeframe context (big picture bias)
👉 So the system behaves like a multi-layer institutional analysis model
Final Summary
The mashup rule system works like this:
It first detects signals independently from volume, price, trend, volatility, and higher timeframe data — then it filters them, then merges them, and finally only allows signals when multiple independent confirmations align.
This is why it is called a confluence-based volume warfare system, not a simple indicator.
Final Note — Ultimate Volume Warfare
This script is designed as a multi-layer market behavior system, not a simple indicator. Its core strength comes from combining volume, price structure, volatility, trend direction, and higher timeframe context into one unified decision framework.
At its foundation, it does not attempt to predict the market. Instead, it waits for confirmation of behavior — meaning it only reacts when multiple independent conditions align. This makes the system more focused on structure and participation rather than noise or emotional price movement.
The divergence engine ensures that price and volume relationships are continuously compared, helping identify situations where the market is losing strength or building hidden continuation pressure. However, because it relies on pivot confirmation, signals are naturally delayed until structure is fully formed. This delay is intentional and represents a shift from prediction-based systems to confirmation-based logic.
The volume classification system adds another layer of intelligence by interpreting raw volume into meaningful market states such as absorption, climax, exhaustion, accumulation, and distribution. This allows traders to understand not just how much volume exists, but what that volume represents in terms of market intent.
On top of this, filters such as EMA trend alignment, ATR volatility validation, and optional higher timeframe confirmation act as protection layers. These filters ensure that signals are only displayed when market conditions are suitable, reducing low-quality setups and improving contextual accuracy.
The mashup architecture is what makes this system unique. Instead of relying on a single signal source, it combines multiple analytical engines that must agree before any trade signal is produced. This creates a confluence-based decision model, where signals represent agreement between different aspects of market behavior rather than isolated indicators.
In practical terms, this means the system prioritizes quality over quantity. Fewer signals may appear, but each one is backed by multiple confirmations across structure, volume, and trend alignment.
Overall, the indicator behaves like a structured market intelligence framework — designed to filter noise, highlight real participation shifts, and provide visually clear confirmation zones for decision-making.
In short: it is not a prediction tool, but a confirmation system that waits for multiple layers of market agreement before showing any trading signal.
Disclaimer — Ultimate Volume Warfare
This indicator is designed strictly for educational and informational purposes only. It is a technical analysis tool that interprets market data such as volume, price structure, volatility, and higher timeframe trends. It does not guarantee results, profits, or accuracy in any market condition.
All signals generated by this script — including buy/sell labels, divergence markers, spike detection, and confluence confirmations — are based on historical and real-time data calculations. These signals are not financial advice, not investment recommendations, and should not be considered as a directive to enter or exit any trade.
Because the system relies on pivot-based structure and confirmation logic, signals may appear with a natural delay. This delay is a known and expected behavior of confirmation-based systems and does not represent prediction capability. Market conditions can change rapidly, and past performance of any signal does not guarantee future outcomes.
The script also uses multiple analytical filters such as trend alignment, volatility checks, and higher timeframe volume comparison. These filters improve contextual accuracy but cannot eliminate market risk. No system is immune to false signals, unexpected volatility, slippage, liquidity gaps, or sudden news-driven movements.
Trading in financial markets involves a high level of risk, and users are fully responsible for their own decisions. You should only use this tool as part of a broader strategy that includes proper risk management, independent analysis, and personal judgment.
The creator of this script does not take responsibility for any financial losses, missed opportunities, or incorrect interpretations resulting from the use of this indicator.
In simple terms: this is a decision-support tool, not a prediction system, and all trading decisions remain entirely the responsibility of the user.
Indicator
Smooths 50 Point LevelsSmooth's 50-Point Levels
Overview
This indicator automatically plots horizontal price levels at every 50-point interval across the chart, centered around the current price. It is designed specifically for futures traders (NQ, ES, MNQ, MES) who use round-number price levels as key reference points for support, resistance, entries, and targets.
How It Works
The indicator calculates the nearest 50-point boundary to the current price using math.round(price / 50) * 50 as its base, then draws a configurable number of levels above and below that base. Levels are split into two distinct categories:
Round Hundreds (X00) — levels ending in 00 (e.g. 19800, 19900, 20000). These represent major psychological price levels where institutional activity and order flow tend to concentrate.
Half-Hundreds (X50) — levels ending in 50 (e.g. 19850, 19950). These act as midpoint references between the major levels, useful for identifying equilibrium zones and scalp targets.
Session Reset
Lines reset visually at a user-defined time each day (default 16:00 ET), meaning the left edge of every line anchors to that bar. This keeps the chart clean and session-specific — only showing levels relevant to the current trading session. A toggle allows lines to be extended further left for historical context.
How To Use
Use Round Hundred levels as primary support/resistance and trade targets
Use Half-Hundred levels as midpoint references and short-term scalp zones
Levels reset at 16:00 ET daily to reflect the new session's relevant price range
Adjust the number of levels displayed to match your trading range
Enable left extension when reviewing previous session price action
Customization
Each level group has independent controls for color, line style (solid/dashed/dotted), line width, label visibility, and label size. Right extension allows lines to project into future bars for forward reference. Indicator
JOAT Pressure Composite [JOAT]JOAT Pressure Composite
Introduction
JOAT Pressure Composite is an open-source accumulation-distribution and participation oscillator built to measure whether buying or selling pressure is strengthening, weakening, rotating, or diverging from price.
It is designed to expose internal sponsorship behind price movement rather than price movement alone.
The script combines weighted close-location flow, relative-volume sponsorship, volume sigma, effort, efficiency, momentum bias, VWAP bias, and confirmed higher-timeframe context into one composite pressure model.
The problem it solves is hidden participation.
Price can rise on weak effort.
Price can fall on poor sponsorship.
Price can continue moving while internal pressure deteriorates.
Pressure Composite tries to expose those changes earlier by measuring how much of the move is actually being sponsored by participation.
The oscillator pane carries the composite, signal line, envelope, flow ribbon, and extreme states.
At the same time, the indicator projects tailored information onto the main chart.
Price divergence is labeled clearly.
Expansion and absorption states are labeled directly on candles.
Anchored VWAP and trend context are overlaid on price so the oscillator and chart remain connected.
Core Concepts
1. Weighted Pressure Engine
The base flow uses close-location value and weighted volume.
closeLocationValue = (2.0 * close - low - high) / barRange
weightedVolume = volume * sponsorshipFactor
2. Pressure Z-Score
The raw pressure series is normalized with a Z-score.
3. Sigma and Effort Layers
Volume sigma and effort help distinguish aggressive participation from ordinary rotation.
4. Efficiency Bias
The script measures whether price is moving efficiently over the selected lookback.
5. VWAP Bias
Distance from anchored VWAP is normalized in ATR terms.
6. Confirmed Divergence Logic
Pivot-based divergence compares oscillator highs and lows to price highs and lows.
7. Expansion and Absorption Labels
The chart prints Bid Expansion, Offer Expansion, Bull Absorption, and Bear Absorption labels directly on price.
8. Confirmed Higher-Timeframe Context
The script pulls confirmed HTF composite states only.
Features
Composite pressure model: blends pressure, effort, sigma, efficiency, and VWAP bias
Flow ribbon: shows whether pressure is widening or fading
Envelope and extreme states: separates normal expansion from aggressive pressure
Confirmed divergence detection: compares oscillator pivots to price pivots
Clear divergence labeling: bullish and bearish pressure divergence is labeled directly on price
Expansion / absorption labels: market states are marked on actual candles
Anchored VWAP context: projected onto the chart for alignment
Fast / slow trend context: price-side guides remain visible while using the oscillator
Confirmed HTF states: non-repainting higher-timeframe pressure context
No dashboard: information is pushed into the chart and oscillator instead of a table
Input Parameters
Composite Engine:
Smoothing Type
Flow Smoothing
Normalization Length
Relative Volume Baseline
Relative Volume Boost
Volume Sigma Length
Effort Smoothing
Efficiency Length
Signal Length
Envelope Length
Envelope Multiplier
Extreme Multiplier
Pivot Length
Divergence Scan
ATR Length
Qualification / Display:
Use Trend Gate
Trend Fast EMA
Trend Slow EMA
Use VWAP Gate
Minimum Spread
Show Histogram
Show Signal Line
Show Envelope
Show Flow Ribbon
Show Divergence
Tint Price Bars
Shade Momentum States
Show Price Context
Show Price Event Labels
How to Use This Indicator
Step 1: Read the composite vs signal relationship to judge widening or fading pressure.
Step 2: Check whether the state is expansion or absorption.
Step 3: Watch labeled divergences closely, especially after extension.
Step 4: Use anchored VWAP and trend overlays to connect the oscillator back to price structure.
Step 5: Use confirmed HTF context as a quality filter rather than a prediction tool.
Indicator Limitations
Divergences can persist before price responds
Confirmed higher-timeframe context intentionally lags unfinished HTF candles
Low-volume environments can flatten the composite even while price drifts
Pressure quality does not guarantee immediate reversal or continuation
Originality Statement
This script is original in how it integrates weighted close-location flow, RVOL sponsorship, sigma, effort, efficiency, VWAP distance, confirmed HTF context, and direct price-chart state labeling into one coherent participation framework.
The components are combined because they all address one question:
how much real sponsorship exists behind current price movement.
Disclaimer
This indicator is provided for educational and informational purposes only.
It is not financial advice.
Pressure readings and divergences do not guarantee reversal or continuation.
Use the script as context and confirmation, not as a promise of outcome.
Best Use Cases
Measuring whether price movement is being sponsored by real participation
Spotting divergence between price and internal pressure
Reading expansion versus absorption conditions
Combining participation context with VWAP and trend structure
Interpretation Notes
The strongest bullish pressure states usually include positive pressure, supportive spread, constructive effort, and favorable price context above value.
The strongest bearish pressure states are the mirror image.
Divergences are most useful when they appear after extension or at major contextual levels.
Absorption labels should be treated as warnings that apparent directional continuation may be losing quality.
Publication Notes
This script is intended to be published with a clean chart where the oscillator, labeled divergence, and at least one price-context label are clearly visible.
Because there is no dashboard, the publication image should make the chart-side annotations easy to read.
Keep the chart clean so the viewer can immediately understand that the script links oscillator behavior back to price.
-Made with passion by jackofalltrades\
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