Normalized Price Transform
Install and import#
npm install fintech-algorithmsimport { normalizedPriceTransform } from "fintech-algorithms/technical-indicators/price-transforms/normalized-price-transform";Signature#
normalizedPriceTransform(input)Converts close into a rolling z-score against its own moving average and standard deviation.
Parameters#
| Name | Type | Notes |
|---|---|---|
input | TopicInput | bars needs timestamp and close. From parameters this topic reads period (default 20, an integer of at least 2). |
Returns#
TopicResult
series holds value, the z-score, alongside the mean and std it was built from; latest carries the last element of each. std is the population standard deviation over the window, and a window whose std is 0 yields a null value while still reporting mean and std. The warm-up is the window.
Warm-up#
The first `period` - 1 bars (19 with the default 20) positions are null. ready_at is 19 on default parameters, set by mean and std becoming available on the same index as value.
Errors#
- When
periodis not an integer of at least 2 — throws Error - When a
closeis not a finite number — throws Error - When fewer than one bar is supplied — 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#
normalizedPriceTransform(input)Returns#
object with 9 fields: topic_id, title, state, ready, ready_at, series, latest, parameters, …
{
"topic_id": "D07-F08-A08",
"title": "Normalized Price Transform",
"state": "calculated",
"ready": true,
"ready_at": 19,
"series": {
"value": [null, null, null, null, null, null],
"mean": [null, null, null, null, null, null],
"std": [null, null, null, null, null, null]
},
"latest": {
"value": -1.9447777278294258,
"mean": 104.20055051999998,
"std": 2.164636086561151
},
"parameters": {},
"diagnostics": {
"causal": true,
"input_count": 96
}
}Diagrams#
Calculation flow#
Normalized Price Transform calculation flow
flowchart LR
A["finite, basis-consistent OHLC observations and any require"] --> B["Validate order, basis, and finite values"]
B --> C["Apply the selected Normalized Price Transform 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"]
Normalized Price Transform 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