SPX Multi-Basis Dashboard[VT]Here is a professional and comprehensive English description tailored for your PulseWire script. You can use this for the script's publication description or as documentation.
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## SPX Multi-Basis Dashboard## Overview
SPX Multi-Basis Dashboard is a high-performance institutional-grade market arbitrage tool designed for Pine Script v6. It calculates and tracks the real-time basis (price discrepancies) among major S&P 500 tracking instruments: SPX, SPY, E-mini Futures (ES!), and Micro E-mini Futures (MES!).
To provide reliable structural market insights and eliminate micro-second price flickering, the dashboard features a 5-minute discrete time-lock mechanism that samples and freezes the basis data at synchronized 5-minute intervals.
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## Key Features
* Strict Non-Rounding Decimal Truncation: Built with custom mathematical routines (math.floor) that strictly truncate all market prices and basis values to 2 decimal places without rounding. This preserves the raw precision required for genuine arbitrage analysis.
* Synchronized 5-Minute Time-Lock: Locks the basis computations every 5 minutes to Filter out minor intraday noise and present clear structural premiums or discounts.
* Explicit Positive/Negative Sign Markings: Automatically appends literal + or - symbols prefixing the basis column (+12.45 / -3.10) for instantaneous visibility of premium/discount states.
* Multi-Symbol Price Cross-Reference: Features a 3-column matrix layouts displaying the tracking Formula, real-time Market Prices, and the 5m Time-Locked Basis side by side.
* Premium Transparent Light Theme: Tailor-made for White/Light chart setups. It features a modern, ultra-clean graphite overlay with variable opacity that naturally blends into your chart workspace without blocking background candlesticks.
* Bulletproof Fault Tolerance: Embedded with v6 native compilation guardrails (ignore_invalid_symbol=true) and strict market cap divergence filters to handle contract rollovers smoothly without breaking or throwing runtime errors.
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## Column Layout Guide
1. Formula: Displays the mathematical alignment rule used for the calculation (e.g., SPX - (SPY × 10) to neutralize the SPY ETF 1:10 split ratio).
2. Market Price: Live streaming quotes fetched directly via unified security channels. (Displays SPX / SPY coupled matrix on row 1, and underlying front-month continuous contract prices for ES! and MES! on rows 2 and 3).
3. 5m Basis: The synchronized basis reading marked in Teal Green for positive values (Premium) and Wine Red for negative values (Discount).
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## Configuration Inputs
* Update Interval (Mins): Customize the basis sampling frequency (Defaults to 5 minutes).
* Dashboard Position: Dynamically anchors the matrix across any corner of your chart workspace (Top Right, Bottom Right, Top Left, Bottom Left).
Indicator
Bitcoin Production Cost | Astral Vision Bitcoin Production Cost | Astral Vision 🌠💠
This indicator estimates the real-world cost of producing one Bitcoin by modeling the energy expenditure of the mining network from on-chain data, then divides by the daily coin issuance to express that cost in USD per BTC. The result is a fundamental price floor reference: sustained trading below the cost of production is historically short-lived because unprofitable miners shut down, reducing hash rate, reducing difficulty, and eventually restoring profitability for those who remain.
Calculation ⚙️
The hash rate is fetched from Glassnode in exahashes per second and converted to terahashes per second. The energy consumption of the network per day is then estimated as: kWh per day = hash rate (TH/s) × efficiency (J/TH) × 86,400 seconds per day / 3,600,000 joules per kWh. This converts the product of hash rate and energy per hash into kilowatt-hours of electricity consumed daily by the entire network.
The hardware efficiency parameter is set dynamically by era rather than using a single static value. Each major mining hardware generation is assigned an approximate efficiency in joules per terahash: 2,000 J/TH before 2014 (early GPU and first-generation ASICs), declining through 800, 500, 250, 100, 85, 55, 40, and 32 J/TH at successive epoch boundaries, with the user-configurable current efficiency applied to recent and future bars. This epoch-based schedule reflects the documented progression of ASIC hardware efficiency over Bitcoin's mining history.
The electricity price is similarly segmented by era, reflecting the documented geographic concentration of mining: a configurable pre-2019 rate for the early period, a lower configurable rate for the Chinese dominance era before the 2021 mining ban, and a configurable post-exodus rate for the current globally distributed mining landscape.
The daily BTC reward available to miners is computed as 144 blocks per day multiplied by the current block subsidy, derived from the block height using the halving schedule, plus daily transaction fees in BTC converted from the CoinMetrics USD fee data. This sum is smoothed with a 7-day SMA to reduce the noise from day-to-day block count variation.
The electricity cost per BTC is then: (kWh per day × electricity price) / daily reward in BTC. This represents what miners spend on electricity alone to produce one Bitcoin. The total production cost divides the electricity cost by the electricity percentage of total costs (default 60% based on CBECI methodology), adding the implicit cost of hardware amortization, facilities, and operations.
The Miner Price is a separate reference: current Bitcoin price plus the USD value of transaction fees per BTC, representing the effective revenue miners receive for each coin equivalent produced. When Miner Price exceeds Total Cost, mining is profitable; when it falls below, miners are operating at a loss.
Plots 📊
Electricity Cost per BTC with glow effect (toggleable)
Total Production Cost per BTC with glow effect (toggleable)
Miner Price with glow effect (toggleable)
Fill between Electricity Cost and Total Cost
Information table with current values for all key metrics: electricity cost, total cost, miner price, BTC price, price-to-total-cost ratio, efficiency, electricity rate, electricity percentage, and block subsidy
Inputs 🎛️
Electricity $/kWh for three historical eras: pre-June 2019, pre-May 2021, and post-May 2021
Electricity percentage of total costs: used to gross up electricity cost to total production cost
Efficiency J/TH: applied to recent and future bars, historical values are set automatically by epoch
Show Electricity Cost, Total Production Cost, Miner Price: individual toggles
Glow effect and info table toggles
Table position: four corner options
Colors 🎨
5 Astral Vision presets + custom override. Default: Infinito.
Purpose 🎯
Standard support and resistance tools are derived entirely from price history and have no connection to the economic reality of Bitcoin production. This indicator derives its reference levels from the physical cost of mining, making it independent of price action and structurally grounded in the economics of the network. The price-to-total-cost ratio in the table provides an immediate reading of how far current price sits above or below break-even for miners, which has historically been one of the most reliable macro cycle indicators available on-chain.
Disclaimer ⭕️
This indicator is for informational and educational purposes only. It does not constitute financial advice. Past performance is not indicative of future results. Always do your own research before making investment decisions. Indicator
Miner Profitability Index | Astral Vision Miner Profitability Index | Astral Vision 🌠💠
This indicator constructs a measure of Bitcoin miner profitability per unit of mining difficulty, then applies Z-Score normalization in log space to quantify how statistically extreme current profitability conditions are relative to their own history. Miner profitability is a structurally important on-chain signal because miners are one of the few participants with predictable and measurable cost structures: when profitability collapses, miners are forced to sell reserves to cover operational costs, creating persistent sell pressure; when profitability is exceptionally high, miners tend to accumulate and expand capacity, which historically precedes periods of increased hash rate and eventually difficulty adjustment that compresses margins back toward equilibrium.
Calculation ⚙️
The daily miner revenue in USD is computed from three components: the number of blocks mined that day (computed as the difference between consecutive daily block height readings from Glassnode), the block subsidy in BTC (derived from the block height using the halving schedule: 50 BTC before block 210,000, halving at each subsequent 210,000-block interval), and the current Bitcoin price in USD. The formula is: miner revenue = blocks per day × block reward × BTC price.
This revenue figure is then divided by the current mining difficulty to produce the efficiency ratio: miner revenue / difficulty. Difficulty represents the computational work required to mine a block and serves as a proxy for the aggregate energy and capital expenditure of the mining network. Dividing revenue by difficulty produces a measure of how many dollars miners earn per unit of computational difficulty, normalizing for the expanding size of the mining network over time. Without this normalization, absolute revenue would grow indefinitely simply due to price appreciation and hash rate expansion, making historical comparisons meaningless.
The efficiency ratio is smoothed with a configurable EMA to reduce the noise introduced by day-to-day variation in block count. The natural logarithm is then taken before applying the Z-Score, which is necessary because the efficiency ratio follows an approximately log-normal distribution: in raw space it would be heavily right-skewed, making the standard deviation an unreliable measure of typical deviation. In log space the distribution is much more symmetric and the Z-Score thresholds carry consistent statistical meaning across all periods.
The Z-Score is computed as: (log(efficiency) - SMA(log(efficiency), N)) / StDev(log(efficiency), N), where N is the configurable lookback window. This expresses how many standard deviations the current log-efficiency sits above or below its rolling historical mean. Two pairs of thresholds define moderate and severe extreme zones on each side.
Plots 📊
Z-Score oscillator colored by zone: two upper levels and two lower levels with graduated opacity
Two upper and two lower threshold lines
Zero midline
Fill highlights when Z-Score is beyond the outer thresholds
Static zone fills between inner and outer thresholds on both sides
Background color on the price chart with four gradient levels reflecting zone severity
Inputs 🎛️
Z-Score Lookback: rolling window for mean and standard deviation normalization
Smoothing: EMA period applied to the raw efficiency ratio before log transformation
Upper Z 1 and Upper Z 2: configurable inner and outer upper threshold levels
Lower Z 1 and Lower Z 2: configurable inner and outer lower threshold levels
Colors 🎨
5 Astral Vision presets + custom override. Default: Futura.
Purpose 🎯
Standard miner revenue charts display absolute USD earnings, which grow indefinitely with price and provide no statistical context for whether current conditions are extreme or normal. Dividing by difficulty removes the network size effect, and normalizing with a Z-Score in log space makes readings directly comparable across all market cycles including early periods when absolute revenue was tiny. The dual threshold system separates mild deviations from statistically severe conditions, providing a more granular signal than a single overbought/oversold level.
Disclaimer ⭕️
This indicator is for informational and educational purposes only. It does not constitute financial advice. Past performance is not indicative of future results. Always do your own research before making investment decisions. Indicator
Logarithmic Mean Reversion Bands | Astral Vision Logarithmic Mean Reversion Bands | Astral Vision 🌠💠
This indicator computes Bollinger Bands in log-price space rather than raw price space, producing a statistically symmetric channel around the geometric mean of Bitcoin's price that correctly represents proportional deviations across all price levels and all market cycles. The oscillator in the sub-panel expresses the current price position in units of standard deviations from the log-mean, providing a normalized reading that is directly comparable regardless of where absolute price is trading.
Calculation ⚙️
The natural logarithm of Bitcoin's daily close price is taken for each bar. A simple moving average of this log-price series is computed over the configurable lookback window, producing the log-mean. The standard deviation of the log-price series over the same window is then computed.
The geometric mean line plotted on the price chart is the exponential of the log-mean: exp(log_mean). This is the geometric mean of price over the lookback window, which differs from the arithmetic mean in a meaningful way for assets with exponential growth trajectories. The geometric mean weights all proportional moves equally, so a period where price doubled from $1,000 to $2,000 contributes the same to the mean as a period where price doubled from $30,000 to $60,000, which is the correct treatment for a multiplicative process like Bitcoin's price.
The four band levels are computed as: exp(log_mean ± n × log_std), where n is 2.0 or 2.5. The exponential conversion ensures the bands are multiplicatively symmetric: the upper band is the same percentage above the geometric mean as the lower band is below it. This symmetry does not hold for standard Bollinger Bands computed on raw prices, where the upper band is a larger percentage above the mean than the lower band is below it.
The oscillator is the standardized log-price deviation: (log_price - log_mean) / log_std. This is dimensionless and equivalent to a Z-Score of the log-price series, measuring exactly how many standard deviations the current log-price sits above or below its rolling mean. A reading of +2.0 means log-price is two standard deviations above its mean, regardless of the absolute price level.
Reversal signals are generated when the oscillator crosses back inside the ±2.0 standard deviation boundary from outside: a downward triangle appears above the bar when the oscillator crosses back below +2.0 after being above it, and an upward triangle appears below the bar when it crosses back above -2.0 after being below it. These signals identify the moment when extreme deviation begins to revert, rather than the moment of maximum extension.
Plots 📊
Geometric mean line on the price chart
Four band lines at ±2.0σ and ±2.5σ on the price chart
Candle coloring on the price chart by band zone: full color outside ±2.5σ, reduced opacity between ±2.0σ and ±2.5σ, neutral between the bands
Z-Score oscillator in the sub-panel with matching ±2.0σ and ±2.5σ reference lines
Fill highlights when oscillator is beyond the outer ±2.5σ level
Static zone fills between the ±2.0σ and ±2.5σ levels
Reversal triangles on the price chart when oscillator crosses back inside the ±2.0σ boundary
Inputs 🎛️
Length: lookback window for the log-mean and log standard deviation
Plot Long/Short Signals: toggle the reversal triangle signals
Colors 🎨
5 Astral Vision presets + custom override. Default: Paradiso.
Purpose 🎯
Standard Bollinger Bands applied to raw Bitcoin price produce bands that are not proportionally symmetric and whose standard deviation readings are not statistically consistent across different price levels. A +2σ reading at $1,000 and a +2σ reading at $50,000 on a raw-price Bollinger Band do not carry the same statistical weight because the distribution of raw price changes is not stationary across Bitcoin's history. Computing the bands in log space corrects this: the log-price distribution is much closer to stationary, making the standard deviation thresholds directly comparable across all cycles. The reversal signals add an entry timing dimension by marking the transition from extreme to normalizing rather than the peak of the extreme.
Disclaimer ⭕️
This indicator is for informational and educational purposes only. It does not constitute financial advice. Past performance is not indicative of future results. Always do your own research before making investment decisions. Indicator
BTC Logarithmic Regression Quantile Bands | Astral Vision Bitcoin Anchored Regression Quantile Bands | Astral Vision 🌠💠
This indicator fits a log-linear regression to Bitcoin's price from a configurable anchor date forward, then constructs a dynamic price channel by mapping the historical quantiles of the regression residuals back into price space. The result is a set of bands that adapt to the actual statistical distribution of how far Bitcoin's price has historically deviated above and below its own long-term trend line, rather than using fixed multipliers or standard deviations.
Calculation ⚙️
The natural logarithm of close is taken for each bar from the anchor date onward. A linear regression is fitted to this log-price series over the full accumulated history from the anchor date up to a configurable maximum bar count, producing a trend line that represents Bitcoin's long-term log-linear growth trajectory from the chosen starting point. Working in log space is essential: Bitcoin's price has expanded across six orders of magnitude, and a linear regression on raw prices would be dominated entirely by recent data. In log space, proportional moves are treated equally across all price levels and all time periods.
The residual at each bar is the difference between the actual log price and the regression trend value: residual = log(close) - trend. This measures in log-space how far price sits above or below its fitted trend at any given moment. A positive residual means price is above trend; a negative residual means price is below trend.
Five quantiles of the residual distribution are then computed over the active history from the anchor date: the 1st and 99th percentiles forming the outer channel, a configurable inner pair (default 5th and 95th) forming the inner channel, and the 50th percentile as the median. Each quantile is converted back to a price level by exponentiating the sum of the trend value and the quantile: band price = exp(trend + quantile). This inversion ensures the bands are always anchored to the current regression trend and scale proportionally with price.
The 50th percentile band represents the median regression price, where historically half of all price observations have been above and half below. The inner bands mark the zone within which the configurable percentage of historical price observations have occurred. The outer 1st and 99th percentile bands mark the historical extremes, where price has spent only 1% of its time beyond each boundary.
Plots 📊
Outer upper band at the 99th percentile of residuals
Inner upper band at the configurable upper quantile
Median band at the 50th percentile
Inner lower band at the configurable lower quantile
Outer lower band at the 1st percentile of residuals
Fills between outer and inner bands on both sides
Background color when price is outside the inner band pair
Bar coloring with six gradient levels reflecting position within the channel
Inputs 🎛️
Anchor Date: starting point for the regression, all quantiles are computed from this date forward
Regression Length: maximum bar count used in the regression and quantile computation
Show Fills: toggle the fill between outer and inner bands
Inner Quantile Pair: percentile level for the inner band pair, symmetric around 50
Colors 🎨
5 Astral Vision presets + custom override. Default: Futura.
Purpose 🎯
Standard Bollinger Bands use a fixed lookback window and assume a normal distribution of price deviations, which does not hold for Bitcoin's log-price residuals. This indicator uses actual empirical quantiles of the full historical residual distribution from the anchor date, making each band level statistically precise: the 99th percentile band has been exceeded by price exactly 1% of the time since the anchor date, which is a more meaningful and verifiable statement than a fixed 2-standard-deviation level. The anchor date architecture also means the bands incorporate the full available price history rather than only a recent rolling window, making them structurally stable references for long-term cycle analysis.
Disclaimer ⭕️
This indicator is for informational and educational purposes only. It does not constitute financial advice. Past performance is not indicative of future results. Always do your own research before making investment decisions. Indicator
Bitcoin WMA Bands | Astral Vision Bitcoin WMA Bands | Astral Vision 💠🌠
This indicator constructs a volatility-adjusted band system around a Weighted Moving Average of price, using the standard deviation of logarithmic daily returns as the volatility measure rather than the standard deviation of price itself. The result is a channel whose width adapts dynamically to the current volatility regime, expanding during high-volatility periods and contracting during low-volatility ones, while remaining anchored to the WMA as the structural fair value reference.
Calculation ⚙️
The base reference line is a Weighted Moving Average of close over a configurable lookback in days. WMA weights recent bars more heavily than older ones using a linearly declining weight schedule, making it more responsive to recent price action than an SMA of the same length while being less erratic than an EMA.
The volatility measure is computed from logarithmic returns: for each bar, the log return is log(close / close ). The standard deviation of these log returns over a configurable lookback window is then multiplied by a configurable scale factor to produce the band half-width `s`. Using log returns rather than raw price changes ensures that the volatility measure is proportional across different price levels, making a 5% move at $10,000 and a 5% move at $100,000 contribute equally to the standard deviation.
The four bands are then computed as: band = WMA × exp(±n × s), where n is 1 or 2. The exponential transformation converts the log-space deviation back to price-space, ensuring the bands are multiplicatively symmetric around the WMA rather than additively symmetric. This means the upper and lower bands are equidistant in percentage terms rather than in absolute dollar terms.
The oscillator in the sub-panel is the log ratio of close to the WMA: log(close / WMA), which measures in log-space how far price has deviated from its trend. The same ±1σ and ±2σ levels are plotted in the sub-panel, allowing direct visual comparison of the oscillator's position within the band structure. Candles on the price chart are colored only when price is outside the ±1σ band, leaving them neutral in the fair value zone between the bands.
Crossover signals are generated when the oscillator crosses back inside the ±1σ boundary from outside: a triangle appears above the bar when the oscillator crosses back below the upper +1σ level from above, and below the bar when it crosses back above the lower -1σ level from below.
Plots 📊
WMA reference line on the price chart
Four volatility-adjusted bands at ±1σ and ±2σ on the price chart
Candle coloring on the price chart when price is outside the ±1σ band
Background color on the price chart between the ±1σ and ±2σ zones
Re-entry signals: triangle above bar on upper band exit, triangle below bar on lower band exit
Log-ratio oscillator in the sub-panel with matching ±1σ and ±2σ reference lines
Inputs 🎛️
STH Length: WMA lookback period in days
StDev Length: rolling window for the log return standard deviation
Band Scale: multiplier applied to the standard deviation before computing band width
Colors 🎨
5 Astral Vision presets + custom override. Default: Paradiso.
Purpose 🎯
Standard Bollinger Bands apply a fixed standard deviation multiple to a simple moving average computed on raw prices, which means the band width in percentage terms varies across different price levels and the bands do not correctly represent proportional deviations. This indicator applies the volatility measure in log-return space and converts back with the exponential function, producing bands that are geometrically consistent across Bitcoin's full price history. The WMA further reduces the lag of the central reference compared to an SMA, making the band system more responsive to trend changes without introducing the instability of shorter lookbacks.
Disclaimer ⭕️
This indicator is for informational and educational purposes only. It does not constitute financial advice. Past performance is not indicative of future results. Always do your own research before making investment decisions. Indicator
Bitcoin MA Quantile Bands | Astral Vision Bitcoin MA Quantile Bands | Astral Vision 🌠💠
This indicator constructs a dynamic price channel around a configurable moving average by computing the statistical distribution of the log ratio between Bitcoin's price and its MA over a long historical lookback, then mapping specific percentiles of that distribution back into price-space bands. The result is a set of bands that adapt to Bitcoin's actual historical price behavior relative to its trend, rather than using fixed multipliers or standard deviations.
Calculation ⚙️
The moving average is computed on daily Bitcoin price data over a configurable length, with an optional 2-day mode that doubles the effective lookback. Five MA types are available: SMA, EMA, WMA, VWMA, and HMA. The Hull Moving Average is computed as WMA(2 × WMA(src, len/2) - WMA(src, len), sqrt(len)), which reduces lag significantly compared to a standard WMA of the same length.
For each bar, the log ratio is computed as log(price / MA). This transforms the multiplicative relationship between price and MA into an additive one, making the distribution symmetric and comparable across different price magnitudes. A price trading 50% above its MA produces the same absolute log ratio as a price trading 50% below, which a raw ratio would not.
Six percentiles of this log ratio series are then computed over the configurable quantile lookback window using linear interpolation: the 1st, 10th, 35th, 65th, 90th, and 99th percentiles. Each percentile is converted back to a price level by multiplying the MA by the exponential of that percentile value: band price = MA × exp(percentile). This inversion ensures the bands are always centered on the current MA value and scale proportionally with price.
The resulting six levels represent: the 1st percentile (historic bottoms, price has been lower than this only 1% of historical bars), the 10th percentile (oversold), the 35th and 65th percentiles (fair value range, price spends roughly 30% of its time between these two), the 90th percentile (overbought), and the 99th percentile (historic peaks).
The indicator can be computed on 1-day or 2-day bars, with the 2-day mode doubling both the MA length and the quantile lookback to maintain structural equivalence.
Plots 📊
Configurable moving average line
Historic Peaks band at the 99th percentile with fill to Overbought
Overbought band at the 90th percentile
Oversold band at the 10th percentile with fill to Historic Bottoms
Historic Bottoms band at the 1st percentile
Inputs 🎛️
Timeframe: 1D or 2D bar mode
MA Length: lookback period for the moving average
MA Type: SMA, EMA, WMA, VWMA, or HMA
Quantile Lookback: historical window over which percentiles are computed
Colors 🎨
5 Astral Vision presets + custom override. Default: Paradiso.
Purpose 🎯
Standard Bollinger Bands use fixed standard deviation multiples, which assume a normal distribution of price deviations around the mean. Bitcoin's price distribution relative to its trend is not normal: it has a heavy right tail during bull markets and periodic extreme downside excursions. Computing bands from actual historical percentiles of the log ratio captures this asymmetry directly, placing the overbought and oversold bands exactly where they have historically been meaningful rather than at a theoretically symmetric distance. The log transformation further ensures that the bands scale correctly with price across Bitcoin's full history, avoiding the distortion that linear band methods produce when comparing early and recent market cycles.
Disclaimer ⭕️
This indicator is for informational and educational purposes only. It does not constitute financial advice. Past performance is not indicative of future results. Always do your own research before making investment decisions. Indicator
Indicator
Volume-Weighted S/R Zones [WillyAlgoTrader]📊 Volume-Weighted S/R Zones is an overlay indicator that automatically detects support and resistance zones from price pivots, scores them by volume and price reaction, tracks breaks and retests, and instantly places a full risk-management plan on the chart with a stop-loss and three take-profits. No manual lines — everything is calculated and drawn automatically.
The core idea: not all levels are equal. A level where price reversed on heavy volume and ran far from it is dozens of times more valuable than a level formed on thin volume with no reaction. The indicator assigns each zone a Strength Score from 0 to 100 , combining volume at the pivot bar, price reaction strength, and touch count — and displays only the zones that actually work.
The indicator is completely free and open-source . Works on any instrument (crypto, forex, stocks, futures, indices) and any timeframe.
🧩 WHY THESE COMPONENTS WORK TOGETHER
A classic pivot indicator draws lines on every local high and low — the chart turns into a mess of dozens of levels, and it's impossible to tell which ones matter. Volume profiles show where heavy trading happened, but don't tie that to specific reversal levels. Pure Price Action gives the right zones, but requires manual markup.
This indicator solves all three problems with one integrated pipeline:
Pivot Detection → Volume Score + Reaction Score → ATR clustering of nearby pivots → Strength Score 0..100 → Age Decay → Break Detection (with filters) → Retest Detection → Zone-Aware SL/TP → Trade Statistics
Each step adds something the previous one cannot. Pivot Detection finds raw reversal points. Volume Score answers the question "was there heavy trading here". Reaction Score answers "did price bounce off the level". ATR clustering merges pivots into a single zone if they sit within N×ATR — giving zone width instead of a thin line. Age Decay gradually reduces the weight of old zones. Break/Retest turn zones into trade signals. Zone-Aware SL places the stop behind the broken zone instead of at an abstract ATR distance. Trade Stats show whether your settings actually work on your instrument.
Remove any component and the system breaks: pivots without scoring are noise, scoring without clustering produces dozens of thin lines, clustering without break/retest gives no signals, signals without zone-aware SL get stopped out on noise.
🔍 WHAT MAKES THIS INDICATOR ORIGINAL
1️⃣ Strength Score 0..100 — three-component zone quality measurement.
Each zone receives a strength score by the formula:
Score = VolScore + ReactionScore + 10 (base bonus), then clamp(0, 100)
Where:
— VolScore (0..40) : computed as min(40, volumeRatio × 20) , where volumeRatio = volume on the pivot bar / average volume over N bars (default 20). On instruments without volume (some forex pairs) a base value of 20 is assigned.
— ReactionScore (0..30) : measured as min(30, max_move / ATR × 10) , where max_move is the maximum price movement AWAY from the pivot in the first N bars after it (default 5). Computed against ATR at the pivot bar, not current ATR — this is the correct normalization.
When the same zone is touched again (a new pivot within ATR × MergeDistance radius, default 0.5), zones merge, the touch counter grows, and a bonus of min(20, √touches × 4) × 0.5 is added to the score. This means: 4 touches give +4, 9 touches +6, 16 touches +8. Logarithmic growth to avoid over-weighting.
Zones are divided into 4 tiers by score: ★ (weak, 0-30), ★★ (medium, 30-60), ★★★ (strong, 60-85), 🔥 (very strong, 85+) . The tier is shown directly on the zone label and affects box transparency — stronger zones are more visually prominent.
2️⃣ Age Decay — old zones lose strength gradually, not abruptly.
Each bar the zone score is reduced by ageDecayRate × 0.1 . By default (0.5) that's −0.05 per bar, so a zone loses about 25 points over 500 bars. This gives an honest forgetting mechanism: a level from last week matters, but not as much as a level from last hour. Can be disabled (set to 0) or made aggressive (1.0 = −0.10 per bar).
Additionally zones are removed by three conditions: age exceeds Max Zone Age (default 30 Days, measured independently of timeframe), score drops below MIN_VIABLE_SCORE = 5.0 , or zone is broken and more than 2×ReactionWindow bars have passed since the break (nobody will retest a stale broken zone).
3️⃣ Break Detection with a dual-volume filter (floor + cap).
The standard "break volume ≥ N×average" filter is easily bypassed by news spikes and gaps. Solution:
— Volume Floor : volume ≥ avg × VolMult (default 1.3) — filters thin-volume breakouts.
— Volume Cap (optional) : volume ≤ avg × VolCap (default 5.0) — filters abnormally large candles (opening gaps, news spikes). Especially important on stocks.
Additionally: Momentum Filter requires the break candle's range to be ≥ N×ATR (default 1.0). This filters "doji breaks" where the candle body barely crossed the level.
4️⃣ Retest Detection with reaction validation.
After a break, the indicator waits for a retest within a Min..Max bars window (default 2..30). A retest counts only if:
— Price touched the broken zone (low ≤ zoneTop for a bullish break)
— Price closed back in trend direction (close > zoneTop)
— Reaction from the zone ≥ ATR × ReactionMin (default 0.5×ATR)
Optionally enable Mitigation Filter , which skips a retest if the zone was already tested once — for traders who only want the first retest.
5️⃣ Zone-Aware Stop-Loss — stops behind real structure, not in thin air.
With Zone-Aware SL enabled, the stop is placed not just at ATR×Mult distance, but by formula:
— For long: SL = max(close − ATR×SLMult, zoneBot − ATR×0.2)
— For short: SL = min(close + ATR×SLMult, zoneTop + ATR×0.2)
The LESS aggressive stop is chosen: either the standard ATR stop, or "behind the zone with a 0.2×ATR buffer". Logic: if the zone is broken, it became resistance (for longs) or support (for shorts). If price returns back INTO the zone — the breakout idea is invalidated, you should exit. This gives a clear exit criterion and usually a wider but more meaningful stop.
6️⃣ Risk presets and three take-profits with partial scaling.
Four ready-made risk presets:
— Conservative : SL 2.5×ATR, TP 1R / 2R / 4R
— Balanced (default): SL 1.5×ATR, TP 1R / 2R / 3R
— Aggressive : SL 1.0×ATR, TP 1.5R / 2.5R / 4R
— Scalping : SL 0.8×ATR, TP 0.8R / 1.5R / 2R
— Custom : configure manually
The model assumes splitting the position into three equal parts: 1/3 on TP1, 1/3 on TP2, 1/3 on TP3. When a TP is touched, the line turns solid cyan with a ✓ checkmark.
7️⃣ Break-Even Trail — after TP1 the stop automatically moves to entry.
With Break-Even After TP1 enabled, on first touch of TP1 the SL is pulled to the entry price. Only TP2 and TP3 remain in play — but the risk is now zero. If price reverses, the trade closes at break-even instead of the original stop. Classic "protect profit, let winners run" model.
Implemented carefully: BE activates only after a confirmed TP1 touch (with no SL break on the same bar), and on the same bar TP1 + SL is always resolved as a stop (conservative model — real brokers don't guarantee limit fills before stops on the same wick).
8️⃣ Session Trade Statistics — tracking real effectiveness.
The dashboard tracks stats right on the chart:
— Trades : total closed trades
— W/L : wins vs losses
— Win Rate : % of wins. A WIN = TP1 reached . This is a deliberate classification: if the idea worked and TP1 closed — that's a success, even if TP2/TP3 didn't fill and exited at BE.
— BE saves : diagnostic counter. How many wins closed via BE-stop rather than TP3. High BE saves ratio → TP3 is set too far.
— Avg R : average R-multiple per trade. Calculated assuming partial scaling (1/3 at each TP).
Stats reset on any settings change (including a dedicated Reset Stats Counter input made specifically for manual resets).
9️⃣ Fully adaptive theme and WCAG-contrast colors.
All colors are calculated for both PulseWire themes (Dark/Light) with WCAG AA contrast verification (4.5:1 minimum). Label text on tinted backgrounds is chosen so it remains readable on both themes. Auto-detection by chart background color, or manual Dark/Light selection in settings.
🔟 TF-independent zone aging.
Max Zone Age can be set in Bars / Hours / Days . This means "30 Days" is always 30 calendar days regardless of timeframe (on 5m it's 8640 bars, on 1h — 720, on 1D — 30). Legacy indicators use bars only, which makes them break when you switch TFs — fixed here.
🧠 HOW IT WORKS — step-by-step calculation flow
Step 1 — Pivot Detection: on each bar, ta.pivothigh and ta.pivotlow are checked with equal left/right lookback (default 21). A pivot is confirmed only after N bars pass — so the indicator does NOT repaint already-drawn zones.
Step 2 — Volume Score: for a confirmed pivot, VolScore is computed against the volume on the pivot bar itself (not the current bar).
Step 3 — Reaction Score: the maximum price movement AWAY from the pivot is measured over the next N bars. ATR at the pivot bar is used for correct normalization.
Step 4 — Merge or Create: if there's already a same-type zone within ATR × MergeDistance — the pivot merges into it (zone widens, score updates, touch counter increments). Otherwise a new zone is created with boundaries ±0.15×ATR from the pivot price.
Step 5 — Age Decay & Cleanup: a reverse pass over the zone array applies decay, removes too-old, too-weak, and stale broken zones. If active zones exceed Max Active Zones — the weakest is removed.
Step 6 — Break Detection: on every confirmed bar, every unbroken zone is checked for a break. Volume Floor, Volume Cap, and Momentum Filter are applied if enabled.
Step 7 — Retest Detection: after a break, a retest with confirmed reaction is searched for in the Min..Max bars window.
Step 8 — Risk Management: on a signal (Break or Retest), with risk management enabled, a virtual position opens with SL and three TPs calculated.
Step 9 — Trade Lifecycle: on each bar, SL/TP touches are checked. TP1 → BE activates. SL or TP3 → position closes, stats update.
Step 10 — Visual & Alerts: zone boxes, SL/TP lines, BRK/RT markers, dashboard — all refresh on the last bar. Alerts fire on bar close.
📖 HOW TO USE — EVEN IF YOU'RE NEW
🎯 Quick start (3 minutes):
1. Add the indicator to your chart (any instrument, any timeframe).
2. Wait 30–50 bars — the indicator needs history for calculations. Zones will appear after that.
3. Look at the dashboard in the top-right corner — it shows current trend, active signal, and position state.
4. Don't change settings on day one. Work with defaults to understand how the indicator "breathes" on your instrument.
5. When you see a BRK or RT signal — look at the horizontal SL/TP1/TP2/TP3 lines. That's your trade plan.
👁️ Reading the chart:
— 🟢 Green box = support zone (Demand). Price approaches from below.
— 🔴 Red box = resistance zone (Supply). Price approaches from above.
— Box transparency = zone strength. The more opaque, the stronger.
— Icon on the label : ★ weak, ★★ medium, ★★★ strong, 🔥 very strong.
— ×N on label = number of zone touches.
— ✕ on label = zone already broken (you can hunt for a retest).
— BRK green below bar = resistance broken upward.
— BRK red above bar = support broken downward.
— RT = confirmed retest of broken level.
— Dotted blue line = entry price of the active trade.
— Solid red line = stop-loss. When it becomes dimmed + ENTRY label says "→ SL (BE)" — stop has moved to break-even.
— Dashed green lines = TP1, TP2, TP3. When they turn solid cyan with ✓ — that TP is reached.
📊 Dashboard (top-right by default):
— Trend : Bullish / Bearish / Neutral. Calculated as weighted difference of zone strength above vs below price.
— Signal : current status (BREAK ▲, RETEST ▼, Long Active, Wait, etc.).
— Score : strength of active signal or strongest zone.
— Zones : number of active zones on chart.
— TF : timeframe.
— SL / TP1 / TP2 / TP3 : risk management prices for the active trade.
— R:R : risk/reward ratio to TP1.
— Risk : % of price you risk to the stop.
— Trades / W/L / Win Rate / BE saves / Avg R : session stats.
🔧 Tuning — what to change and when:
— Too many zones, chart cluttered: raise Min Score to Display to 30–40. Raise Zone Merge Distance to 0.7–1.0.
— Too few zones: lower Pivot Lookback to 10–15. Lower Min Score to 0–10.
— Scalping 1m–5m: use Scalping preset, Pivot Lookback 5–8, ATR Length 10.
— Swing 1h–4h: Balanced preset, Pivot Lookback 21 (default), Max Zone Age 30 Days.
— Position trading 1D: Conservative preset, Pivot Lookback 10–15, Max Zone Age 90 Days.
— False breakouts eat your account: enable Volume Filter for Breaks + Momentum Filter.
— Trading stocks/indices with gaps: keep Volume Cap on (it's on by default).
— Want only the first retest: enable Mitigation Filter for Retests.
— Frequently closing at BE without profit: check BE saves in dashboard. If >50% of wins — TP3 is too far, shorten it.
💡 Trading ideas:
— Most reliable setup: retest of a strong zone (★★★ or 🔥) in the dashboard trend direction .
— Don't trade against the strongest zone (🔥) in your path — wait for it to break first.
— A zone touch without confirmed reaction is NOT a signal. The indicator filters this for you, but don't try to "guess" the bounce in advance.
— Use Trade Stats as feedback. If after 50 trades Win Rate < 40% and Avg R < 0 — change settings or timeframe.
⚙️ KEY SETTINGS
⚙️ Main Settings:
— Pivot Lookback (default 21): how many bars on each side must be lower/higher for a pivot
— Max Active Zones (default 8): max number of active zones on chart
— Zone Merge Distance (default 0.5×ATR): merge radius for nearby pivots
— Min Score to Display (default 15): hide zones weaker than this
📦 Zone Detection:
— ATR Length (default 14): ATR period for all calculations
— Volume Avg Lookback (default 20): average volume window
— Reaction Window (default 5): bars to measure reaction after a pivot
— Age Decay Rate (default 0.5): zone aging speed
— Max Zone Age (default 30 Days): maximum zone age
— Max Zone Age Unit (Bars / Hours / Days)
🔍 Filters (optional):
— Volume Filter for Breaks (default off): require volume ≥ N×average on break
— Volume Multiplier (default 1.3)
— Volume Cap (default on, 5.0): filter abnormal spikes
— Momentum Filter (default off): require candle range ≥ N×ATR
— Mitigation Filter (default off): first retest only
🎯 Signals:
— Show Break Signals / Show Retest Signals
— Min/Max Bars for Retest (default 2 / 30)
— Min Retest Reaction (default 0.5×ATR)
🛡️ Risk Management:
— Enable Risk Management (default on)
— Risk Preset (Conservative / Balanced / Aggressive / Scalping / Custom)
— SL ×ATR , TP1/TP2/TP3 ×Risk (for Custom)
— Zone-Aware SL (default on): place stop behind the zone
— Break-Even After TP1 (default on)
— Show SL/TP Lines / Labels
— Show % Distance on Labels
— Entry/SL/TP Line Style (Solid / Dashed / Dotted)
🎨 Visual:
— Theme (Auto / Dark / Light)
— Show Zones / Score Labels / Watermark
— Zone Forward Bars (default 5): how many bars to project zones forward
— SL/TP Label Font Size , Signal Marker Size
📊 Dashboard:
— Show Dashboard , Position
— Show Trade Stats (W/L, Win Rate, Avg R, BE saves)
— Reset Stats Counter : changing the value resets stats
🔔 ALERTS
— 🟢 BREAK UP — resistance broken upward, with price, score, SL, and three TPs
— 🔴 BREAK DOWN — support broken downward
— 🟢 RETEST LONG — confirmed long retest
— 🔴 RETEST SHORT — confirmed short retest
— 🎯 TP1 / TP2 / TP3 HIT — target reached (optional)
— 🛑 SL HIT / 🛡️ BE STOP-OUT — stop-loss hit or break-even close
— 🛡️ BREAK-EVEN ACTIVATED — stop moved to entry
All alerts available in two formats: plain text (readable for Telegram/Discord) and JSON (for webhook automation). Fire on bar close (alert.freq_once_per_bar_close) — no intra-bar flooding.
⚠️ IMPORTANT NOTES
— 🚫 No repainting. All signals use barstate.isconfirmed. Pivots are confirmed with equal left/right lookback — meaning the pivot point is always N bars in the past. This is delayed confirmation, not repainting of future values. Zones don't move after they appear.
— 📐 Zones are built from confirmed pivots. This means a zone appears on the chart N (Pivot Lookback) bars after the extreme formed. On the most recent 21 bars to the right there will be no zones — this is normal and correct.
— ⚖️ On instruments without volume (some forex pairs, some indices) VolScore defaults to 20 out of 40. Zone quality scoring is lower than on crypto/stocks with real volume.
— 🛠️ This is an analysis tool, not an automated bot. The indicator finds zones, marks signals, and proposes a structured trade plan — but entry decisions are YOURS. Past performance does not guarantee future results.
— 📊 Trade Stats counts virtual trades based on indicator signals, without slippage, commissions, or real liquidity. Use as a reference, not as a promise of results.
— 🌐 Universal compatibility: works on any ticker and timeframe. On tick/Renko charts, Hours/Days options for Max Zone Age automatically fall back to 500 bars.
— 💯 Completely free, open-source. Study the code, fork it, modify it for yourself.
If you found this indicator useful — leave a 🚀 and follow the author profile to see updates and new publications. Questions and feedback welcome in the comments. Indicator
Vesper Structure Ledger [JOAT]Vesper Structure Ledger
Introduction
Vesper Structure Ledger is an open-source market structure indicator built around KAMA trend context, pivot-based BOS and CHoCH events, liquidity sweeps, equal high/low probes, premium/discount zones, demand/supply boxes, right-side structural rails, managed signal boxes, and a top-right dashboard.
The script is intended to make structure easier to read without relying on arrows or cluttered labels. It distinguishes continuation structure from potential character shifts, then adds trend, impulse, volume, and higher-timeframe context before qualifying stronger events.
Core Concepts
1. KAMA Trend Core
The KAMA engine uses an efficiency ratio to adapt smoothing. When price moves efficiently, the trend line responds faster. In noisy conditions, it slows down and reduces whipsaw sensitivity.
2. Pivot Structure Memory
Confirmed pivot highs and lows are stored as structural references. These levels become the next possible break points for BOS or CHoCH events.
// Conceptual summary
// pivot high and pivot low become current structure rails
// confirmed closes through those rails create BOS or CHoCH events
3. BOS vs CHoCH
A Break of Structure confirms continuation in the current structural direction. A Change of Character marks a break against that direction and can signal a potential shift. Vesper also tracks BOS counts before allowing some character changes to carry more weight.
4. Sweeps and Equal Levels
Liquidity sweeps occur when price probes beyond a swing level and closes back through it. Equal high and equal low probes mark nearby repeated liquidity levels.
5. Demand/Supply and Managed Structure Map
Confirmed qualified signals can create demand or supply zones and a managed visual box with entry, invalidation, and target levels. These levels are for context and planning only.
Features
Adaptive KAMA trend line: Efficiency-ratio smoothing for trend context
BOS and CHoCH logic: Separates continuation breaks from possible character shifts
BOS-count gating: Adds context before stronger reversal interpretation
Liquidity sweeps: Detects confirmed wick-and-reclaim events around swing levels
Equal high/low probes: Marks repeated nearby liquidity levels
Premium/discount fill: Shows position inside the recent structure range
Demand and supply boxes: Projects reaction zones from qualified structure
Right-side rails: Labels KAMA, swing high, swing low, and equilibrium
Managed signal box: Displays entry, invalidation, and target levels
Top-right dashboard: Shows trend, KAMA, slope, structure, BOS count, sweep, equal level, context, impulse, targets, and state
Input Parameters
Trend Core:
KAMA Length
Fast Period
Slow Period
Source
Structure Core:
Pivot Left and Pivot Right
Structure Objects
Show BOS
Show CHoCH
Show Target Lines
Liquidity Core:
Show Liquidity Sweeps
Sweep Lookback
Sweep Buffer ATR
Show Equal Levels
How to Use This Indicator
Step 1: Read trend context
Use KAMA and the dashboard trend row to understand whether price is above or below the adaptive trend.
Step 2: Watch BOS and CHoCH
BOS events suggest continuation. CHoCH events warn that character may be changing.
Step 3: Mark liquidity
Sweeps and equal-level probes identify areas where price has tested or reclaimed liquidity.
Step 4: Use zones as references
Demand/supply boxes and right-side rails help frame current structure. They are not automatic entries.
Indicator Limitations
Pivot-based structure confirms after the right-side pivot window completes
CHoCH events can fail in strong continuation markets
Sweeps require confirmed closes and may appear after the wick forms
Zone boxes are contextual references, not assurances of support or resistance
Originality Statement
Vesper Structure Ledger combines adaptive KAMA trend state, pivot structure, BOS/CHoCH classification, BOS-count context, sweep logic, equal-level probes, premium/discount mapping, projected demand/supply boxes, and managed structure rails in one open-source Pine v6 tool. The purpose is to create a cohesive structure ledger, not a collection of unrelated labels.
Disclaimer
This script is for educational and informational use only. It is not financial advice and does not predict future market behavior. Always use independent analysis and risk management.
-Made with passion by jackofalltrades
Indicator
Stochastic Bot with SL/TPStochastic Momentum Bot with Risk Management
Description
This trading bot is an automated strategy designed for PulseWire. It aims to capitalize on short-term price reversals by identifying when an asset is temporarily "oversold" (priced too low) or "overbought" (priced too high) using the Stochastic Oscillator.
Unlike basic indicator scripts that simply highlight buy and sell signals on a chart, this is a full Strategy Script. This means it virtually executes trades using historical data, applying strict Stop-Loss (SL) and Take-Profit (TP) percentages to protect your capital.
It is highly customizable, allowing you to fine-tune the parameters to suit different assets and timeframes.
How the Logic Works
Entry (Buy): The bot enters a Long position when the %K line crosses above the %D line, but only if both lines are below the 20 threshold (indicating the asset is heavily oversold and momentum is shifting upward).
Exit 1 (Take Profit): The bot will automatically close the trade if the price rises by your set Take-Profit percentage.
Exit 2 (Stop Loss): The bot will automatically cut its losses and close the trade if the price drops by your set Stop-Loss percentage.
Exit 3 (Momentum Reversal): If neither the SL nor TP is hit, the bot will close the trade early if the %K line crosses below the %D line while above the 60 threshold (indicating the asset is overbought and momentum is dying).
Step-by-Step Guide to Using the Bot
Part 1: Loading the Script into PulseWire
Open PulseWire and load the chart you want to trade (e.g., TAO/USDT on the 15-minute timeframe).
At the very bottom of the screen, click on the Pine Editor tab.Delete any existing code in the editor window so it is completely blank.
Copy the Pine Script code provided previously and paste it into the editor.
Click the Save button (floppy disk icon) at the top right of the Pine Editor and give your script a name (e.g., "Stochastic Bot").
Click the "Add to Chart" button.
Part 2: Customizing the Strategy SettingsOnce the script is on your chart, a new menu will appear at the top left of your chart area with the name of your script.Hover over the script's name and click the Gear Icon (Settings).Click on the Inputs tab.
Here is what each setting controls:
Setting Name
Default
Description
%K Length14
The number of previous candles used to calculate the main momentum line.%K Smoothing3Smooths out the %K line to reduce false signals.%D Smoothing3The moving average of the %K line, used as the trigger line for crossovers.
Stop Loss (%)2.5
The maximum percentage of price drop you are willing to risk before exiting a trade.
Take Profit (%)6.0
The percentage of price increase required to automatically lock in profits and exit.
Part 3: Reading the Strategy Tester
Once the bot is on your chart, the Strategy Tester tab at the bottom of the screen will automatically populate with backtesting data based on your current settings and timeframe.
Net Profit: The total amount of money the bot made (or lost) over the given time period.
Total Closed Trades: How many times the bot bought and sold.
Percent Profitable (Win Rate): The percentage of trades that ended in a profit.
Max Drawdown: The largest percentage drop in your account balance from its peak. This is a crucial metric for understanding risk; a high drawdown means the bot experienced severe losing streaks.
List of Trades: A tab inside the Strategy Tester that shows you every single historical entry, exit, and the exact price it triggered at. Strategy
Put Credit Spread Combined Price Tracker📊 Description
The Put Credit Spread Combined Price Tracker is an advanced options visualization and risk assessment workspace designed specifically for multi-position credit spread sellers. Instead of guessing your proximity to risk, this indicator maps your mathematical break-even thresholds directly onto your live asset candle chart while maintaining a real-time Black-Scholes Options Pricing Matrix Dashboard.
This tool is ideal for tracking individual or nested index options structures (such as SPX, NDX, or RUT) where precision risk boundary management is critical.
________________________________________
⚙️ How to Set Up Your Spreads
1. Add to Chart: Load the indicator on your target ticker (e.g., SPX).
2. Open Settings: Click the gear icon on the indicator name to open the configuration menu.
3. Configure Your Engine:
o Keep Enable Automated Volatility checked to let the script automatically extract a continuous historical volatility proxy, or uncheck it to key in your broker's implied volatility (IV %) reading manually.
4. Input Your Positions (Supports up to 4 Parallel Trades):
o Check the Box to enable a specific spread position.
o Short/Long Put Strike: Key in your exact leg boundaries.
o Premium Received: Enter the net premium collected per spread block (e.g., 5.00 for a $500 credit).
o Contracts Quantity: Enter your position size.
o Start/Exp Date: Key in your precise calendar execution parameters. The indicator automatically bounds the line drawings to your trade's specific lifecycle window.
________________________________________
📉 Reading the Chart Visuals
• Dashed Break-Even Lines: The script removes clutter by stripping out raw strike lines. Instead, it plots the absolute net financial break-even floor for each position (Short Strike - Premium Collected). If the market candles drop below this dashed line at expiration, the position enters a net loss state.
• Right-End Anchored Labels: Each active position features a dedicated text flag pinned directly to the right margin of your screen, letting you instantly match a specific break-even line to its designated position entry.
________________________________________
🧮 Understanding the Dashboard Table (Bottom-Right)
The tracking matrix evaluates your positions dynamically using a full Black-Scholes Options Pricing model loop on every price tick:
• Strikes (S/L): Displays your structured position boundaries for quick auditing.
• Current Mark: Shows what the option spread is worth right now in the open market before expiry, modeling continuous time decay (\(\theta \)) and underlying spot movements.
• Live Open P&L: Replicates your broker's dashboard. It dynamically updates using (Net Credit - Current Mark Value) * 100 * Qty. Cells turn Green for an open profit and Red for an open loss.
• Position Delta: Displays your aggregate Greeks exposure. Since put credit spreads are directionally bullish, this value will calculate as a net positive number.
• Current IV: Shows the exact annualized volatility proxy percentage fueling your options pricing calculations.
• Days Left: Counts down the exact localized time window remaining before contract expiration.
________________________________________
Indicator
Stoch RSI Golden Cross | Astral Vision Stoch RSI Golden Cross | Astral Vision 🌠💠
This indicator applies a Stochastic RSI computed on a fixed 5-day timeframe, using deliberately long lookback periods that filter out short-term noise and produce a slowly-turning oscillator oriented toward identifying major cycle inflection points rather than frequent trading signals. Crossovers between the K and D lines are only considered valid when they occur within the oversold or overbought zones, ensuring that signals correspond to genuine momentum reversals from extreme positioning rather than midrange noise crosses.
Calculation ⚙️
The RSI is computed over 121 periods on the 5-day timeframe. The Stochastic of that RSI is then computed over 144 periods, measuring where the current RSI value sits within its highest-to-lowest range over the past 144 bars. This raw Stochastic is smoothed with a 33-period simple moving average to produce the K line. A second 25-period simple moving average is then applied to K to produce the D signal line.
The use of a 5-day timeframe with these long periods means each bar represents one trading week, and the full K lookback of 144 bars covers approximately 2.75 years of weekly data. This makes the oscillator insensitive to anything shorter than multi-month momentum shifts, functioning as a macro cycle tool rather than a swing trading indicator.
A bullish golden cross signal fires when K crosses above D while both lines are below the oversold threshold (default 10), meaning the crossover occurs from a position of statistically extreme pessimism. A bearish cross signal fires when K crosses below D while both lines are above the overbought threshold (default 80), meaning the crossover occurs from a position of statistically extreme optimism. Crosses that occur in the neutral zone between the two thresholds are ignored entirely.
Each valid signal draws a vertical line with a four-layer glow effect on the price chart, marking the exact bar at which the signal occurred and extending across the full chart height for maximum visibility.
Plots 📊
K line in the sub-panel
D signal line in the sub-panel
Oversold threshold line at 10
Overbought threshold line at 80
Glow vertical lines on the price chart at each valid bullish cross
Glow vertical lines on the price chart at each valid bearish cross (toggleable)
Inputs 🎛️
Show Only Bullish Golden Cross: toggle to hide bearish cross signals and show only bullish ones
Colors 🎨
5 Astral Vision presets + custom override. Default: Inferno.
Purpose 🎯
A standard Stochastic RSI with default parameters (14/14/3/3) generates dozens of signals per year, most of which are noise on a macro timeframe. This implementation uses a 5-day bar combined with extended lookback periods to reduce the signal count to a handful per multi-year cycle, corresponding only to the deepest oversold recoveries and most extreme overbought reversals. The zone filter adds a second condition that eliminates all midrange crosses, further concentrating the signal set on statistically meaningful structural turning points. The result is an indicator designed to fire rarely and only at potentially significant macro inflection points rather than as a continuous trading signal generator.
Disclaimer ⭕️
This indicator is for informational and educational purposes only. It does not constitute financial advice. Past performance is not indicative of future results. Always do your own research before making investment decisions. Indicator
OTHERS/USDT.D Z-Score | Astral Vision OTHERS/USDT.D Z-Score | Astral Vision 🌠💠
This indicator constructs a ratio between the OTHERS market cap dominance and USDT dominance, then applies Z-Score normalization in log space to measure how statistically extreme the current positioning of altcoin capital relative to stablecoin dry powder is compared to its own history.
OTHERS dominance tracks the combined market cap share of all cryptocurrencies excluding Bitcoin, Ethereum, and the top few large caps, making it a direct proxy for altcoin season conditions. USDT dominance measures the share of total crypto market cap held in Tether, which rises when capital exits risk assets into stablecoins and falls when stablecoin capital is deployed into crypto assets.
Calculation ⚙️
The ratio is computed as OTHERS dominance divided by USDT dominance on a daily timeframe. A high ratio means altcoin capital is large relative to stablecoin reserves, indicating that available dry powder has been deployed and the altcoin market is extended. A low ratio means stablecoin dominance is high relative to altcoin exposure, indicating that capital has retreated to safety and dry powder is accumulating.
The natural logarithm of this ratio is then taken before all subsequent calculations. Working in log space normalizes the exponential growth of both series across different market cycles, ensuring that a ratio change from 2 to 4 is treated as equivalent in magnitude to a change from 4 to 8, which is the correct treatment for proportional dominance relationships.
A simple moving average and standard deviation are computed over the configurable Z-Score lookback window, producing the Z-Score as: (log ratio minus mean) / standard deviation. This expresses the current ratio in units of standard deviations above or below its own historical average, making readings directly comparable across cycles regardless of the absolute dominance levels involved.
In Trend mode, an EMA of configurable length is applied to the Z-Score itself, functioning as a signal line. When the Z-Score is above its EMA, the momentum of the ratio is positive and altcoin conditions are improving relative to stablecoin reserves; when below, the momentum is negative.
Plots 📊
Z-Score oscillator colored by mode and regime
Two upper threshold lines marking statistically elevated altcoin exposure (Extremes mode)
Two lower threshold lines marking statistically depressed altcoin exposure (Extremes mode)
Fill highlights when Z-Score enters the outer extreme zones
Zero baseline
EMA signal line (Trend mode)
Background color on the price chart when Z-Score enters the outer extreme zones (Extremes mode)
Candle coloring on the price chart reflecting current regime in both modes
Inputs 🎛️
Visualization: Extremes or Trend
Z-Score Lookback: normalization window for mean and standard deviation
Upper Z 1 and Upper Z 2: configurable inner and outer upper threshold levels
Lower Z 1 and Lower Z 2: configurable inner and outer lower threshold levels
EMA Length: smoothing period for the trend signal line (Trend mode)
Colors 🎨
5 Astral Vision presets + custom override. Default: Futura.
Purpose 🎯
Standard altcoin season indicators use fixed dominance thresholds or simple moving average crossovers on raw dominance values, which are not statistically normalized and behave differently across cycles as the total crypto market cap grows. This indicator normalizes the ratio in log space over a long rolling window, making a Z-Score of +2.0 in 2021 and a Z-Score of +2.0 in 2024 carry equivalent statistical weight despite the absolute dominance percentages being different. The dual threshold system further separates moderate elevated conditions from statistically severe ones, allowing a more nuanced reading than a single overbought/oversold line can provide.
Disclaimer ⭕️
This indicator is for informational and educational purposes only. It does not constitute financial advice. Past performance is not indicative of future results. Always do your own research before making investment decisions. Indicator
Bitcoin Vaulted Price Decay Bands | Astral Vision Bitcoin Vaulted Price Decay Bands | Astral Vision 🌠💠
This indicator constructs a dynamic price channel around a concept called the Vaulted Price: a modified version of Bitcoin's Realized Price that weights the on-chain cost basis by a measure of how much of the supply is being held long-term rather than actively circulating. The resulting bands adapt over time to reflect both the evolution of Bitcoin's aggregate cost basis and the changing proportion of supply held by long-term conviction holders.
Calculation ⚙️
The Realized Price is normally computed as Realized Cap divided by total supply, where Realized Cap values each coin at the price it last moved on-chain rather than at current market price. This indicator modifies that baseline by introducing a vaultedness coefficient derived from the percentage of Bitcoin that has not moved in over one year. The formula is: vaultedness = 0.5 + (active1y / 100) × 1.0, where `active1y` is the percentage of supply active within the past year fetched from Glassnode. This coefficient scales between 0.5 and 1.5, amplifying the Realized Cap when more supply is actively circulating and compressing it when more supply is dormant. The Vaulted Price is then: Realized Cap × vaultedness / total supply.
The upper band applies a time-decaying multiplier to the Vaulted Price: top multiplier = base × days^exponent, where days is the number of days elapsed since June 13, 2011, the reference origin for this model. Because the exponent is negative (default -0.35), the multiplier shrinks over time following a power law, meaning the upper band converges toward the Vaulted Price as Bitcoin matures. This captures the empirically observed compression of Bitcoin's peak-to-realized-price ratio across successive market cycles. The lower band applies a fixed multiplier to the Vaulted Price, providing a stable support reference scaled to the cost basis of long-term holders.
Each band is rendered with three layered plots at decreasing transparency and increasing line width, producing a glow effect.
Plots 📊
Upper band: Vaulted Price multiplied by a time-decaying power law coefficient, with three-layer glow
Lower band: Vaulted Price multiplied by a fixed support multiplier, with three-layer glow
Inputs 🎛️
Top Multiplier Base: starting magnitude of the upper band multiplier before time decay
Top Decay Exponent: rate at which the upper multiplier compresses over time, negative values produce decay
Bottom Multiplier: fixed multiplier applied to the Vaulted Price for the lower support band
Colors 🎨
5 Astral Vision presets + custom override. Default: Inferno.
Purpose 🎯
Standard realized price and cost basis indicators treat all supply equally regardless of whether coins have been dormant for years or moved yesterday. This indicator separates the two by weighting the cost basis by the activity ratio of supply, producing a reference price that reflects the aggregate conviction of holders who are choosing not to sell rather than the average of all coins including those being actively traded. The time-decaying upper band further addresses a limitation of fixed-multiplier models, which overstate the distance to cycle tops in later cycles when Bitcoin's absolute price is orders of magnitude higher than in earlier cycles. The decaying exponent makes the upper band structurally tighter in each successive cycle, consistent with Bitcoin's historically compressing peak-to-cost-basis ratio.
Disclaimer ⭕️
This indicator is for informational and educational purposes only. It does not constitute financial advice. Past performance is not indicative of future results. Always do your own research before making investment decisions. Indicator
AHR999 | Astral Vision AHR999 | Astral Vision 🌠💠
This indicator computes the AHR999 index, a composite valuation metric that combines two independent measures of Bitcoin's price position: its distance from a geometric moving average of recent price, and its distance from a long-term power law growth model based on Bitcoin's age in days. When both measures agree that price is depressed, the index produces low readings historically associated with strong accumulation opportunities.
Calculation ⚙️
The first component is the ratio between current Bitcoin price and its geometric mean over a configurable lookback window. Unlike an arithmetic mean, the geometric mean multiplies all values together and takes the N-th root, making it more representative of compounded growth and less sensitive to extreme price spikes. To keep the numbers computationally manageable, the daily close is scaled by dividing by 10,000 before computing the geometric mean, then rescaled afterward. The ratio of current price to this geometric mean measures whether price is above or below its recent compounded average.
The second component is the ratio between current price and a power law estimate of Bitcoin's fair value derived from its age. The power law estimate is: estimated price = 10 ^ (5.84 × log10(bitcoin age in days) + (-17.01)), where bitcoin age counts from the genesis block. This formula captures the empirically observed relationship between Bitcoin's price and the time elapsed since its creation, producing a continuously rising fair value line that reflects Bitcoin's historical growth trajectory. The ratio of current price to this estimate measures how far price sits above or below its age-implied fair value.
The AHR999 index is then the product of these two ratios: geometric mean ratio multiplied by power law ratio. Historically, readings below approximately 0.45 have corresponded to strong accumulation zones, while readings above 1.2 have corresponded to elevated valuation. A configurable oversold level controls when the index triggers the accumulation signal, and the corresponding price level at which the index would reach that threshold is plotted directly on the price chart as a dynamic support reference.
The price overlay band is derived by inverting the AHR999 formula: given a target index value of `os_level`, the implied price is the square root of (`os_level` × geometric mean price × estimated power law price).
Plots 📊
AHR999 index line colored by position relative to the oversold threshold
Oversold threshold line in the sub-panel
Dynamic price level on the chart corresponding to the oversold threshold
Background color highlight in the sub-panel and on the price chart when index is below threshold
Candle coloring with continuous gradient reflecting the index value
Inputs 🎛️
Length: lookback window for the geometric mean calculation
Oversold Level: index threshold below which accumulation conditions are signaled
Colors 🎨
5 Astral Vision presets + custom override. Default: Paradiso.
Purpose 🎯
Standard moving average crossovers or RSI-based oversold signals measure Bitcoin's price relative only to its own recent history, without any reference to the long-term growth trajectory implied by its age and adoption curve. The AHR999 index introduces a second reference frame — the power law model — making it possible to distinguish between price being temporarily below its short-term average in a bull market versus being genuinely depressed relative to its structural long-term fair value. The dynamic price band on the chart further operationalizes this by showing in price terms exactly where the accumulation threshold currently sits, rather than requiring the user to mentally translate an oscillator reading back into a price level.
Disclaimer ⭕️
This indicator is for informational and educational purposes only. It does not constitute financial advice. Past performance is not indicative of future results. Always do your own research before making investment decisions. Indicator
VWAP + Key Levels SignalsVWAP + Key Levels Signals
A multi-timeframe price-action signal tool for futures traders. It marks
BUY and SELL signals when price reacts at an institutional reference level
in agreement with VWAP bias and candle conviction.
WHAT IT PLOTS
The indicator auto-calculates and tracks the key levels that price tends to
react to:
- Daily, 4H and 1H 50/200 SMAs
- Prior Day High/Low (PDH/PDL)
- Prior Globex Session High/Low (PSH/PSL — default 18:00–08:00)
- 1H Fibonacci retracements (.382 / .50 / .618 / .786)
- Unmitigated 1H swing highs/lows formed on above-average volume
- Session VWAP — used as the directional bias filter, not as a tradeable level
HOW A SIGNAL IS FORMED
A signal only prints when ALL of the basic conditions line up on the same
1-minute candle:
1. Price is AT a key level (within the touch buffer).
2. The move is IN CONFORMITY WITH VWAP bias (price on the correct side of
VWAP and/or VWAP sloping the right way — selectable).
3. The candle reacts in the direction of the bias — a green candle closing
above the level for longs, a red candle closing below it for shorts.
4. The candle is decisive (optional strong-body / volume filters).
When that 1-minute candle CLOSES in the bias direction, the signal fires:
green triangle = BUY, red triangle = SELL. Signals are confirmed on bar
close — they do not repaint.
SUGGESTED RULES OF ENGAGEMENT
- Entry: on the close of the signal candle, in the direction of the signal.
- Stop loss: at the key level that triggered the signal (place it just
beyond — e.g. a few ticks past the level).
- Target: the next key level in the direction of the trade. Manage the
runner manually or trail behind structure.
A NOTE ON SIGNAL FREQUENCY
Because the tool watches many levels across several timeframes, it can
produce a high number of signals — this is by design. Each one simply marks
that the basic conditions were met at that moment. Use the VWAP bias mode,
the touch buffer, and the strong-candle/volume filters to tighten the feed
to only the highest-conviction reactions. Start loose to see everything,
then filter down to your taste.
PAIRS WITH "HTF Levels + Volume-Filtered Unmitigated Swings"
This signal tool is designed to be used alongside the companion indicator
"HTF Levels + Volume-Filtered Unmitigated Swings." Both calculate the same
reference levels with the same logic, so the lines on your chart will match
the levels the signals fire from. Run the HTF Levels indicator for the
visual map and this tool for the reactions — or hide this tool's lines
(Display → Plot KPL levels OFF) and let the HTF Levels indicator draw them.
SETTINGS TO START WITH
- KPL touch buffer: 0.5 points (loosen to 1.0 on volatile days)
- VWAP Bias Mode: "Price vs VWAP" to start; "Price + Slope" for the
strictest, cleanest setups
- Require strong candle: ON (min body 50%)
- Apply to a liquid futures contract on a 1m or 5m chart with enough
history loaded for the higher-timeframe SMAs to populate
ALERTS
Built-in BUY and SELL alert conditions — set them from the alert menu for
push/email notification on a fresh signal.
──────────────────────────────────────────
DISCLAIMER
This is a free, open-source educational tool. It is NOT financial, investment
or trading advice and makes no promise or guarantee of profit. Signals are
informational only and may produce losing trades. Trading futures involves
substantial risk of loss and is not suitable for every investor. Past
performance and historical signals are not indicative of future results.
Always backtest and forward-test on a demo account, and trade your own plan
with your own risk management. You are solely responsible for your trading
decisions. Indicator
Quantum Pulse AI V6 [Nifty AI Scalper]High-Level Overview
This script is a hybrid trading system that combines traditional trend-following indicators with a k-Nearest Neighbors (k-NN) Machine Learning engine. Instead of relying solely on hardcoded crossovers, it looks at the current market conditions, searches its historical memory for similar moments, and predicts the next move based on what happened in the past.
1. The Technical Foundation (Base Features)
Before the AI even kicks in, the script tracks a robust baseline of institutional-grade metrics:
Moving Averages: Two customizable MAs (SMA/EMA/VWMA) determine short-term momentum.
VWAP & Bands: Anchored daily VWAP with up to 3 standard deviation bands to judge institutional value and overbought/oversold extremes.
Trend Smoothing: Hull Moving Average (HMA) and Supertrend dictate the broader directional bias.
Momentum Filters: ADX ensures the market is actually trending (ignoring chop), while relative volume tracks participation.
2. The AI k-NN Classification Engine
This is the "brain" of the script. It uses a mathematical algorithm to predict price direction based on Euclidean geometry.
Feature Vectors: It takes 4 real-time data points (MA spread, Price vs. VWAP, HMA slope, and Relative Volume) and normalizes them into a 4-dimensional spatial grid.
Historical Scanning: The script looks back in time (e.g., 2,000 bars) and calculates the exact geometric distance between the current market conditions and historical market conditions.
Voting System: It isolates the k closest historical matches (e.g., the 8 most similar moments in the past). It then looks at what price actually did next in those historical moments (went up or went down). Those neighbors "vote" on the current probability, generating a Bull/Bear Confidence Percentage.
3. Signal Filtering & State Tracking (Anti-Flicker)
The script includes strict logic to prevent chart clutter and false signals:
Convergence: A signal will only fire if the AI probability is above your defined threshold (e.g., 70%), the ADX shows a strong trend, and price is structurally on the correct side of the VWAP.
State Tracker: A built-in memory state (currentTradeState) forces strict alternation. Once an "AI BUY" fires, the system locks into a Long state. It will ignore any duplicate bullish spikes and will only fire again when an "AI SELL" conditions are met.
4. Dashboards & UI
Core Dashboard: A bottom-center panel that gives a rapid visual summary of all traditional metrics (Price, VWAP, MA, HMA, ST, ADX, Volume).
ML Ensemble Panel: A top-right heads-up display showing the AI's exact live confidence percentages, its grading scale (A+, A, B, C), and the current active forecast.
Day Trading Extras: Automatically plots Previous Day High/Low/Close, daily Pivot points, Support/Resistance levels, and the critical First 15-Minute High/Low breakout zones. Indicator
Cobalt Session Ledger [JOAT]Cobalt Session Ledger
Introduction
Cobalt Session Ledger is an open-source intraday context indicator focused on session VWAP, synthetic volume delta, liquidity sweeps, absorption, and managed visual trade mapping. It is designed to help users read whether current price action is extending, reverting, sweeping liquidity, or building pressure around the active session's value area.
The script uses a modern dark chart style with cyan, teal, red, amber, and violet accents. It includes VWAP sigma bands, session CVD, sweep and absorption markers, candle coloring, reward/risk boxes, right-side entry/stop/target labels, and a top-right dashboard.
Core Concepts
1. Session VWAP and Sigma Bands
The session engine accumulates price-volume data during the configured session and computes VWAP. It also derives deviation bands around VWAP so price can be evaluated in sigma terms rather than raw distance.
// Conceptual summary
// VWAP = cumulative price * volume / cumulative volume
// sigma bands = VWAP +/- session deviation multiples
2. Synthetic Delta and Session CVD
Because PulseWire symbols often lack true bid/ask delta, the script estimates directional pressure from candle body position, close position, range, and volume. That value is accumulated into a session CVD line and smoothed for dashboard and signal context.
3. Liquidity Sweep Detection
Confirmed sweeps occur when price probes beyond a recent swing high or low and closes back through it with directional rejection. These events are shown with clean square/circle markers rather than arrows.
4. Absorption and Wick Skew
Absorption combines volume expansion, compact candle range, and close location. Wick skew helps describe whether rejection is occurring from the upper or lower side of the candle.
5. Managed Ledger Map
When a confirmed ledger signal appears, the indicator can draw a reward zone, risk zone, entry line, stop line, and T1/T2/T3 targets at the right edge. These are visual planning aids, not executed orders.
Features
Session VWAP engine: Uses the configured session and timezone
VWAP sigma rails: Displays inner and outer VWAP deviation shells
Session CVD: Tracks synthetic volume pressure during the session
Liquidity sweeps: Detects confirmed reclaim/rejection events around recent pivots
Absorption markers: Highlights volume compression and close-location absorption
Confidence scoring: Combines VWAP, delta, structure, absorption, volume, and session context
Managed trade map: Draws entry, stop, T1, T2, T3, reward box, and risk box
Candle tinting: Colors bars based on confidence and directional pressure
Top-right dashboard: Shows VWAP, CVD, delta, liquidity, confidence, sigma, entry, targets, and session range
Confirmed-bar signals: Ledger signals are gated with barstate.isconfirmed
Input Parameters
Session:
Session Window
Session Timezone
Liquidity and Absorption:
Liquidity Pivot Length
Volume Spike Multiplier
Absorption Range Ceiling
Bull/Bear Absorption Close Bias
Trade Map:
Show Managed Trade Map
Show Right-Side Price Labels
Trade Box Projection Bars
Target 1, 2, and 3 R multiples
Signal Cooldown Bars
How to Use This Indicator
Step 1: Start with VWAP
Read whether price is above, below, or stretched from session VWAP.
Step 2: Confirm pressure
Use the CVD and delta rows to determine whether volume pressure supports the price location.
Step 3: Watch sweeps and absorption
Sweep and absorption events can mark potential exhaustion or reclaim zones.
Step 4: Treat trade boxes as planning overlays
The ledger box gives a structured visual reference for risk and reward. It does not ensure that the market will reach any level.
Indicator Limitations
Synthetic delta is an estimate, not true exchange bid/ask delta
Signals are session-context tools, not automatic trade instructions
Quiet symbols and low-volume sessions can reduce signal quality
The managed trade map is visual only
Originality Statement
Cobalt Session Ledger combines session VWAP sigma analysis, synthetic CVD, sweep/reclaim logic, absorption detection, wick skew, confidence scoring, candle tinting, and managed visual trade mapping into a single open-source Pine v6 session tool. The components work together to classify session pressure and price location rather than act as unrelated overlays.
Disclaimer
This script is for educational and informational use only. It is not financial advice or a recommendation to buy or sell any instrument. Trading involves risk, and historical context does not ensure future behavior.
-Made with passion by jackofalltrades
Indicator
80-20 Levels (NQ)80-20 Levels (NQ) plots psychological round-number price levels for Nasdaq futures (NQ) and color-codes them relative to VWAP. The idea: prices ending in .80 and .20 (e.g. 28,780.00, 29,520.00) act as recurring magnet/reaction zones intraday. Pairing them with VWAP gives you instant context on whether each level sits in "premium" (above VWAP) or "discount" (below VWAP) territory.
What it does
80/20 levels — draws horizontal lines at every price ending in .80 and .20, automatically re-centered around live VWAP as price moves.
VWAP-relative coloring — levels above VWAP are red, levels below VWAP are green, so bias is readable at a glance.
VWAP line — standard intraday session VWAP (resets each session), plotted in orange.
Price-axis labels — each level's price prints as a color-matched tag directly on the right-hand price scale.
New York session range box — a table showing the total NY session range (high − low) plus the session high/low, in the corner of your choice.
Settings
Setting Description
Levels past VWAP (each side) How many 80/20 levels to show on each side of VWAP. e.g. 4 = 4 green levels below VWAP and 4 red levels above (1–10).
Show VWAP Show/hide the VWAP line.
Show price-axis labels Show/hide the per-level price tags on the right axis.
Above VWAP color Color for levels above VWAP (default red).
Below VWAP color Color for levels below VWAP (default green).
Level line width Thickness of the level lines (1–4).
Show NY session range Show/hide the session-range box.
Range box position Corner/edge for the box (Top Right, Top Center, Top Left, Middle Right/Left, Bottom Right/Center/Left).
Range box size Text size: Tiny / Small / Normal / Large / Huge.
New York session Session window (default 0930-1600).
Session timezone Default America/New_York.
⚠️ Required setup: enable price-axis labels
The level price tags use Pine's display.price_scale, which only renders if the chart's price scale has value labels enabled. This is a one-time chart setting, not part of the script — so include this in your published description:
Right-click the price scale (the price axis on the right edge of the chart).
Hover Labels in the menu that appears.
Click "Indicators and financials value labels" so it shows a checkmark.
The red/green level tags will appear on the axis immediately. If this option is off, the levels still draw on the chart but the axis price tags won't show.
Notes: this is a per-chart/layout setting and applies to all indicators' value labels, so you'll need to enable it on any new chart where you add the indicator. The indicator's own "Show price-axis labels" toggle controls whether this indicator contributes tags.
Suggested use
Designed for NQ (also works on MNQ / NQ1!). The .80/.20 logic assumes NQ's price magnitude; on very different instruments the spacing won't be meaningful.
Best on intraday timeframes where VWAP and the NY session are relevant.
Watch for reactions as price approaches a level; use the red/green VWAP context to frame whether you're fading into premium or buying discount. Indicator
Aurelian Consensus Bands [JOAT]Aurelian Consensus Bands
Introduction
Aurelian Consensus Bands is an open-source price consensus map built around a log-volume profile, dynamic consensus bands, VWAP context, and confirmed-bar signal logic. It is designed to answer a specific question: where is price trading relative to the market's recent volume-weighted agreement zone, and is that move supported by session pressure?
The script plots VPOC, consensus area, boundary bands, session VWAP deviation shells, a dynamic volume node, right-side price rails, managed signal boxes, candle coloring, and a compact top-right dashboard. Its goal is not to predict the future. It provides a structured chart layer for reading acceptance, rejection, and directional pressure around consensus levels.
Core Concepts
1. Log-Volume Consensus Profile
The script builds a rolling profile on a logarithmic price canvas. Recent bars contribute volume across high-low rows, with recency weighting applied before the profile is converted into levels. This reduces sensitivity to one-off spikes while preserving important volume clusters.
// Conceptual summary
// volume is distributed across log-price rows
// rows are then analyzed for VPOC, mean, and stdev bands
2. VPOC, CA, and Boundary Band
The engine extracts a volume point of control, consensus area high/low, and wider boundary bands. The midpoint of the consensus area and the VPOC can be blended into the active anchor. Price displacement from that anchor is normalized so the indicator can classify whether price is inside, above, or below the agreement zone.
3. Dual-Anchor Coherence
Aurelian compares the VPOC view and consensus-area midpoint view. Signals are only stronger when both views agree. If the two anchors conflict, the coherence score falls and the dashboard shows weaker context.
4. VWAP and Session Pressure
The script adds session VWAP, VWAP deviation shells, synthetic delta pressure, and a dynamic volume node. Qualified signals require more than a simple cross; they also consider whether VWAP and pressure agree with the band event.
5. Right-Side Price Rails and Signal Box
The current VPOC, anchor, consensus levels, VWAP, and dynamic node are projected to the right edge with price labels. Qualified signals can also create a managed visual box with entry, stop, T1, and T2 levels based on ATR and planned R multiples.
Features
Rolling log-volume profile: Builds VPOC, consensus area, and boundary bands from recent price-volume structure
Dual-anchor coherence filter: Compares VPOC and consensus midpoint before qualifying signals
VWAP deviation shells: Adds session VWAP context and upper/lower deviation bands
Dynamic volume node: Tracks a lighter-weight volume anchor for current conditions
Candle color blending: Colors bars using consensus direction and institutional context strength
Qualified signal markers: Uses clean dots/squares rather than arrows or retail-style markers
Managed signal box: Projects entry, stop, T1, and T2 for visual planning only
Right-side rails: Labels VPOC, anchor, CA high/low, VWAP, and node prices at the chart edge
Top-right dashboard: Shows mode, bias, coherence, score, VWAP state, delta, node, quality, and state
Confirmed-bar logic: Main signal events are gated on confirmed bars
Input Parameters
Profile Core:
Profile Rows controls profile resolution
Profile Lookback controls how much recent history is used
Recency Weight Span controls how quickly old bars lose influence
Profile Smooth controls smoothing on extracted levels
Context and Rails:
Show Session VWAP and VWAP Deviation Shells
Show Dynamic Volume Node
Show Right-Side Price Rails
Show Managed Signal Box
Signal Stop ATR Mult and Target R settings
How to Use This Indicator
Step 1: Read the anchor
Use the VPOC and consensus anchor to understand where the market's recent agreement zone sits.
Step 2: Check coherence
Higher coherence means the VPOC and consensus midpoint agree. Lower coherence suggests mixed structure.
Step 3: Watch VWAP and node context
Signals carry more context when price, VWAP, delta, and the dynamic node point in the same direction.
Step 4: Use right-side rails
The rails provide forward reference levels for continuation, rejection, or mean reversion planning.
Indicator Limitations
The profile depends on the selected lookback and row resolution
Signals are contextual, not standalone trade recommendations
Very low volume symbols may produce less reliable profile and delta readings
Confirmed-bar logic means signals appear after the bar closes, not before
Originality Statement
Aurelian combines a rolling log-volume consensus profile, dual-anchor coherence, session VWAP deviation context, synthetic pressure, dynamic node tracking, right-edge rails, and managed visual signal boxes in one open-source Pine v6 tool. The purpose is not to merge unrelated indicators, but to create a single acceptance/rejection framework around volume agreement and session context.
Disclaimer
This script is for educational and informational use only. It is not financial advice and does not ensure any trading outcome. Market behavior is uncertain, and all signals should be evaluated with risk management and independent judgment.
-Made with passion by jackofalltrades
Indicator
Indicator
Structure Delivery Radar [JOAT]Structure Delivery Radar
Introduction
SDR Structure Delivery Radar is an open-source market structure overlay that classifies short-term, intermediate-term, and long-term delivery using confirmed pivots, break events, sweep events, session position, and ATR compression.
The indicator is designed as a structural context layer. It does not try to predict every candle. Instead, it tracks whether price is delivering through meaningful structure levels and whether multiple structure tiers are aligned.
Core Concepts
1. Three-Tier Structure
The script tracks ST, IT, and LT swing highs and lows from confirmed pivots. Each tier keeps its own bias state.
2. Confirmed Breaks
A bullish break requires a confirmed close above the tracked swing high. A bearish break requires a confirmed close below the tracked swing low.
3. Sweep Detection
The script recognizes when price trades beyond a swing level but closes back through it, marking potential liquidity behavior without using future bars.
4. Delivery Score
The dashboard score blends structure alignment, break activity, sweep activity, session location, and ATR compression into a 0-100 reading.
5. Clean Structure Cloud
The visual output uses transparent clouds and dashboard states rather than cluttered arrows or excessive labels.
Features
ST/IT/LT structure tracking: Three independent confirmed-pivot layers
Break and sweep logic: Official events require confirmed bars
Delivery score: Quantifies structure alignment and current delivery state
Session cloud: Adds session range context
Structure cloud: Shades the active upper/lower structure region
Top-right dashboard: Shows tier bias, events, ranges, compression, ATR, and signal state
Alerts: Includes bullish and bearish delivery confirmations
Input Parameters
Structure:
ST Pivot Length
IT Pivot Length
LT Pivot Length
ATR Length
Session and Visuals:
Use Session Window
Show Session Cloud
Show Structure Cloud
Show Bias Tint
Cloud and background transparency
How to Use
Step 1: Check whether the dashboard shows BULL, BEAR, or NEUT for the dominant structure state.
Step 2: Read the delivery score. Higher scores indicate stronger alignment across the internal model.
Step 3: Treat sweep events as context for failed breaks or liquidity reactions.
Step 4: Use the structure cloud as a map of active structural boundaries.
Limitations
Pivot-based structure confirms after the pivot length has passed
The score is a context reading, not a guarantee of trade outcome
Compressed markets can delay structure continuation
The script should be combined with risk management and execution rules
Originality Statement
SDR is an original JOAT implementation combining multi-tier confirmed structure, sweep recognition, session context, ATR compression, and a delivery score into one Pine Script v6 overlay.
Disclaimer
This script is for educational and informational purposes only. It is not financial advice and does not guarantee future results. Trading involves risk, and users should apply their own risk management.
Made with passion by jackofalltrades
Indicator
