Accumulation/Distribution Oscillator [MarkitTick]💡 This script presents a statistically normalized evolution of the classic Accumulation/Distribution (A/D) indicator, designed to transform unbounded volume flow into a bounded, actionable oscillator. By integrating Relative Volume (RVOL) weighting and Z-Score standardization, this tool isolates genuine institutional buying and selling pressure from market noise, offering a clear view of volume momentum regimes.
✨ Originality and Utility
The standard Accumulation/Distribution line is a cumulative total of volume flow, which often results in an unbounded line that drifts indefinitely with price trends. This makes it difficult for traders to identify overextended conditions or specific turning points.
This script solves that problem through a three-stage quantitative process:
Smart Volume Weighting: Instead of treating all volume equally, this indicator amplifies the impact of high-volume nodes using a Relative Volume (RVOL) filter. This ensures that significant institutional activity carries more weight than low-liquidity chopping.
Detrending: It subtracts a smoothed average (using ALMA, EMA, or others) from the raw A/D line to create a raw oscillator.
Normalization: Finally, it applies a Z-Score calculation to normalize the data. This bounds the oscillator around a zero mean, allowing for the application of Bollinger Bands to detect statistical extremes (2 or 3 standard deviations).
🔬 Methodology and Concepts
The calculation logic follows a strict quantitative pipeline:
● Money Flow Multiplier (MFM)
The core engine is the classic MFM calculation, which determines the location of the Close relative to the High-Low range. A Close near the High results in +1, while a Close near the Low results in -1.
● Advanced Volume Filtering
Before accumulation, the volume is processed through two filters:
RVOL Multiplier: If the current bar's volume exceeds its simple moving average (`rvol_len`), the volume is multiplied by a user-defined factor (`rvol_mult`). This emphasizes breakout candles.
Candle Strength (Optional): If enabled, weight is increased based on how close the price closes to the absolute high or low, rewarding decisive candle shapes.
● Z-Score Standardization
The script calculates the "Raw Oscillator" by subtracting a moving average (Signal Line) from the cumulative A/D Line. It then calculates the Z-Score of this raw value over a lookback period (`z_len`).
Formula: Z = (Value - Mean) / Standard Deviation
🎨 Visual Guide
The indicator renders a complex data set into an easy-to-read interface:
• The Oscillator (Line & Histogram)
The primary output is the Z-Score value.
Teal Histogram/Line: Represents Bullish momentum (Accumulation). Darker Teal indicates accelerating momentum (`osc > previous`), while lighter Teal indicates decaying momentum.
Red Histogram/Line: Represents Bearish momentum (Distribution). Darker Red indicates accelerating selling pressure, while lighter Red indicates exhaustion.
Gray: If the Trend Filter (200 EMA) or VWAP Filter is enabled and the signal opposes the trend, the histogram turns Gray to indicate a low-probability counter-trend signal.
• Bollinger Bands (Blue Bands)
These bands wrap around the oscillator line.
Upper Band: Usually set to +2 Standard Deviations. When the oscillator pierces this band, accumulation is statistically extreme (potential mean reversion or strong breakout).
Lower Band: Usually set to -2 Standard Deviations. Indicates statistically extreme distribution.
• Divergences
The script automatically detects and plots structural divergences:
Green Lines/Labels: Bullish Divergence. Price makes a Lower Low while the Oscillator makes a Higher Low.
Red Lines/Labels: Bearish Divergence. Price makes a Higher High while the Oscillator makes a Lower High.
• Multi-Timeframe (MTF) Dashboard
Located in the top right, this table displays the momentum status (BULL/BEAR) of the oscillator across three user-defined timeframes (default: 60min, 240min, Daily), allowing for fractal trend analysis.
📖 How to Use
This tool is best used for identifying trend exhaustion and hidden volume strength.
1. Trend Continuation
In a strong uptrend, look for the Histogram to remain Teal and above the Zero line. A pullback to the Zero line that bounces back up suggests buyers are stepping in to defend the trend.
2. Statistical Extremes
When the oscillator line breaks outside the Bollinger Bands, volume flow is significantly deviated from the norm.
If price is ranging, this often signals a reversal (Reversion to Mean).
If price is breaking out, this confirms strong impulse participation.
3. Divergence Reversals
A divergence is a leading signal. If price is pushing new highs but the A/D Oscillator fails to make a new high (Red Divergence Line), it indicates that the volume supporting the move is drying up, often preceding a correction.
⚙️ Inputs and Settings
● Oscillator Settings
Smoothing Type/Length: Choose between ALMA, EMA, SMA, etc., to smooth the A/D line. ALMA is default for its zero-lag properties.
ALMA Offset/Sigma: Fine-tune the responsiveness of the Arnaud Legoux Moving Average.
● Quant Filters
RVOL Lookback & Multiplier: Determines the threshold for "High Volume." Default is 1.5x average volume.
Z-Score Lookback: The period used to establish statistical significance (Default: 100).
Use VWAP/Trend Filter: Logical switches to gray out signals that contradict the macro trend (200 EMA) or the intraday mean (VWAP).
● Dashboard
Customize the three timeframes displayed in the MTF table to match your trading horizon (e.g., Scalpers might use 5m, 15m, 1h).
🔍 Deconstruction of the Underlying Scientific and Academic Framework
This indicator relies on the Law of Supply and Demand quantified through Standard Score (Z-Score) Statistics .
Standard Accumulation/Distribution is derived from the work of Marc Chaikin, positing that the proximity of the close to the high/low on high volume indicates the "smart money" flow. However, raw cumulative data suffers from heteroscedasticity (varying variance).
By applying Z-Score normalization:
Z = (x - μ) / σ
We transform the data into a standard normal distribution. This allows us to apply probability theory to volume analysis. A value of +2.0 is not merely "high"; it represents a volume flow intensity that falls within the top 2.2% of the data set (assuming normal distribution), providing a mathematically robust definition of "Overbought" or "Oversold" volume conditions.
⚠️ Disclaimer
All provided scripts and indicators are strictly for educational exploration and must not be interpreted as financial advice or a recommendation to execute trades. I expressly disclaim all liability for any financial losses or damages that may result, directly or indirectly, from the reliance on or application of these tools. Market participation carries inherent risk where past performance never guarantees future returns, leaving all investment decisions and due diligence solely at your own discretion.
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