Volume-Weighted MACD
Install and import#
npm install fintech-algorithmsimport { volumeWeightedMacd } from "fintech-algorithms/technical-indicators/volume-indicators/volume-weighted-macd";Signature#
volumeWeightedMacd(input)Runs the MACD construction on volume-weighted moving averages of close instead of exponential ones, and smooths the resulting line into a signal.
Parameters#
| Name | Type | Notes |
|---|---|---|
input | TopicInput | bars needs timestamp, close and volume. From parameters this topic reads fast_period (default 3), slow_period (default 10, minimum fast_period + 1) and signal_period (default 9, an integer of at least 2). |
Returns#
TopicResult
series holds value, the fast VWMA of close minus the slow VWMA, and signal, the EMA of value over signal_period. latest carries the last element of each. A window whose volume sums to 0 makes that VWMA null, which propagates. The two warm-ups differ and are described below.
Warm-up#
The first `slow_period` - 1 bars for `value` (9 with the defaults); a further `signal_period` - 1 for `signal` (index 17) positions are null. ready_at is 9, driven by value. signal is still null there, so a crossover strategy needs the later index.
Errors#
- When
slow_periodis not an integer greater thanfast_period— throws Error - When
signal_periodis not an integer of at least 2 — throws Error - When a bar carries a negative
volume— throws Error
Complexity: time O(n),
space O(n).
Worked example#
executed Captured by running this function on the input its own test provides. Real output of real code — but not asserted against a published figure.
Input#
{
"bars": [
{
"timestamp": "2024-01-02",
"basis": "synthetic-unadjusted",
"open": 100,
"high": 101.45,
"low": 98.695,
"close": 100,
"volume": 750000,
"benchmark": 200
},
{
"timestamp": "2024-01-03",
"basis": "synthetic-unadjusted",
"open": 101.49111452,
"high": 103.38381693,
"low": 100.05480022,
"close": 101.78791214,
"volume": 795117,
"benchmark": 200.56326135
},
{
"timestamp": "2024-01-04",
"basis": "synthetic-unadjusted",
"open": 102.45519048,
"high": 104.6701838,
"low": 100.91147007,
"close": 102.9549389,
"volume": 840234,
"benchmark": 201.11020913
}
],
"parameters": {}
}Call#
volumeWeightedMacd(input)Returns#
object with 9 fields: topic_id, title, state, ready, ready_at, series, latest, parameters, …
{
"topic_id": "D07-F05-A19",
"title": "Volume-Weighted MACD",
"state": "calculated",
"ready": true,
"ready_at": 9,
"series": {
"value": [null, null, null, null, null, null],
"signal": [null, null, null, null, null, null]
},
"latest": {
"value": -2.799155032079767,
"signal": -1.3105571933842994
},
"parameters": {},
"diagnostics": {
"causal": true,
"input_count": 96
}
}Diagrams#
Calculation flow#
Volume-Weighted MACD calculation flow
flowchart LR
A["basis-consistent OHLCV observations with venue/session cov"] --> B["Validate order, basis, and finite values"]
B --> C["Apply the selected Volume-Weighted MACD convention"]
C --> D["Emit value, readiness, and diagnostics"]
D --> E["Interpret descriptively; test outcomes separately"]
B -->|invalid or insufficient| X["Withhold output with a reason"]
Volume-Weighted MACD readiness and evidence states
stateDiagram-v2
[*] --> Waiting
Waiting --> Ready: enough valid causal observations
Waiting --> Rejected: malformed or unsupported input
Ready --> Calculated: selected formula applied
Calculated --> Interpreted: diagnostic and limitation retained
Interpreted --> Ready: next observation arrives
Rejected --> Waiting: corrected input and deterministic reset
How it works#
This page states the contract — how to call it correctly. The article explains the concept: why it works, and where it breaks.
References#
- TA-Lib function groups — see linked primary or authoritative record
- TA-Lib C/C++ API — see linked primary or authoritative record
- TA-Lib maintained source — see linked primary or authoritative record
- Evidence decision
- Level 1 evidence map