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QuanTAlib/lib/volume/adl/Adl.md
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# ADL: Accumulation/Distribution Line
> "Volume precedes price." — Old Wall Street Adage
The Accumulation/Distribution Line (ADL) is the bedrock of volume analysis. It attempts to answer a single, vital question: "Are the big players buying or selling?"
Unlike On-Balance Volume (OBV), which treats every up-day as 100% buying, ADL is nuanced. It looks at *where* the price closed within the day's range. A close near the high on massive volume screams "Accumulation." A close near the low on massive volume screams "Distribution."
## Historical Context
Developed by Marc Chaikin, the ADL was originally designed to spot divergences. Chaikin noticed that if a stock made a new high but the ADL failed to make a new high, a crash was imminent. He essentially quantified the "smart money" flow.
## Architecture & Physics
ADL is a cumulative indicator, meaning it has infinite memory. Today's value depends on the sum of all yesterdays.
The core mechanic is the **Money Flow Multiplier (MFM)**, also known as the Close Location Value (CLV). This value ranges from -1 to +1:
- **+1**: Close = High (Maximum Accumulation)
- **-1**: Close = Low (Maximum Distribution)
- **0**: Close is exactly in the middle
This multiplier is then applied to the volume to determine the "Money Flow Volume" for the period.
## Mathematical Foundation
### 1. Money Flow Multiplier (MFM)
$$
MFM = \frac{(Close - Low) - (High - Close)}{High - Low}
$$
### 2. Money Flow Volume (MFV)
$$
MFV = MFM \times Volume
$$
### 3. Accumulation/Distribution Line (ADL)
$$
ADL_t = ADL_{t-1} + MFV_t
$$
## Performance Profile
| Metric | Score | Notes |
| :--- | :--- | :--- |
| **Throughput** | 10 | High; O(1) calculation with simple arithmetic. |
| **Allocations** | 0 | Zero-allocation in hot paths. |
| **Complexity** | O(1) | Constant time per update. |
| **Accuracy** | 10 | Matches all standard libraries exactly. |
| **Timeliness** | 10 | No lag; updates immediately with each bar. |
| **Overshoot** | N/A | Cumulative indicator; concept doesn't apply. |
| **Smoothness** | 2 | Jagged; reflects raw volume and price location. |
## Validation
| Library | Status | Notes |
| :--- | :--- | :--- |
| **QuanTAlib** | ✅ | Validated. |
| **TA-Lib** | ✅ | Matches `TA_AD` exactly. |
| **Skender** | ✅ | Matches `GetAdl` exactly. |
| **Tulip** | ✅ | Matches `ad` exactly. |
| **Ooples** | ✅ | Matches `CalculateAccumulationDistributionLine`. |
### Common Pitfalls
- **Gaps**: ADL ignores gaps. If a stock gaps up but closes near its low, ADL will register distribution, even if the price is higher than yesterday.
- **Scale**: The absolute value of ADL is meaningless; it depends on the start date of the data. Only the *trend* and *divergence* matter.
- **Volume Spikes**: A single bad data point with erroneous volume can permanently skew the ADL. Sanitize your data.