Vertical Horizontal Filter
Install and import#
npm install fintech-algorithmsimport { verticalHorizontalFilter } from "fintech-algorithms/technical-indicators/trend-systems/vertical-horizontal-filter";Signature#
verticalHorizontalFilter(input)Divides the highest-to-lowest close span over a window by the sum of the absolute bar-to-bar close changes in that same window, separating directed movement from back-and-forth movement.
Parameters#
| Name | Type | Notes |
|---|---|---|
input | TopicInput | bars is the OHLCV series, validated for finite prices, strictly increasing timestamp, a single adjustment basis, non-negative volume, and a high and low that bracket the other prices. From parameters this topic reads only period (integer, minimum 2, default 14), the length of both the close extremes and the absolute change sum. |
Returns#
TopicResult
series and latest carry a single value key. A bar is null when the summed absolute change is zero, that is when every close in the window is identical, since that would divide by zero. The warm-up is one window.
Warm-up#
The first period - 1 bars (13 by default) positions are null. Both the extremes and the change sum need a full window, so with the default period indices 0 to 12 are null and ready_at is 13.
Errors#
- When
parameters.periodis present but is not an integer of at least 2 — throws Error - When
barsis empty, or a bar has a non-finite price, a negative volume, a timestamp not greater than the previous one, or a high below its open, low, or close — throws Error
Complexity: time O(n * period),
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#
verticalHorizontalFilter(input)Returns#
object with 9 fields: topic_id, title, state, ready, ready_at, series, latest, parameters, …
{
"topic_id": "D07-F02-A15",
"title": "Vertical Horizontal Filter",
"state": "calculated",
"ready": true,
"ready_at": 13,
"series": {
"value": [null, null, null, null, null, null]
},
"latest": {
"value": 0.6258523821746035
},
"parameters": {},
"diagnostics": {
"causal": true,
"input_count": 96
}
}Diagrams#
Calculation flow#
Vertical Horizontal Filter calculation flow
flowchart LR
A["ordered OHLC or close observations with explicit window, s"] --> B["Validate order, basis, and finite values"]
B --> C["Apply the selected Vertical Horizontal Filter 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"]
Vertical Horizontal Filter 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