# Time Order, Frequency, Regularity, and Financial Calendars

`D00-F10-A01` · Financial Mathematics, Statistics, and Data Foundations → Financial Time-Series Foundations · archetype `record-transform` · difficulty 1/5 · verification **verified**

Full page: https://docs.thefintechbuilder.com/foundations/financial-time-series-foundations/time-order-frequency-regularity-and-financial-calendars/
Agent skill: `npx skills add IslamBaraka90/Fintech-Algorithms-Library` — https://docs.thefintechbuilder.com/guides/agent-skill/

## Install and import

```bash
npm install fintech-algorithms
```

```ts
import { timeOrderFrequencyRegularityAndFinancialCalendars } from "fintech-algorithms/foundations/financial-time-series-foundations/time-order-frequency-regularity-and-financial-calendars";
```

## Signature

```ts
timeOrderFrequencyRegularityAndFinancialCalendars(input)
```

Checks whether a timestamped series runs in chronological order and whether its observations are evenly spaced, reporting the common spacing in seconds when there is one.

## Parameters

| Name | Type | Required | Notes |
| --- | --- | --- | --- |
| `input` | `D00Input` | yes | Reads `timestamps`, a list of parseable date-time strings, and `values`, a non-empty list of finite numbers of the same length. Only the timestamps drive this calculation; the values supply the count. |

## Returns

`D00Output`

`ordered` is true when no timestamp precedes the one before it, `regular` is true when every consecutive gap is identical, `observations` is the series length, and `frequencySeconds` is that common gap in seconds or `null` when the spacing varies.

## Errors

- When `values` is absent, empty, or holds a non-finite number — throws RangeError
- When `timestamps` and `values` have different lengths — throws RangeError
- When the series holds fewer than two observations — throws RangeError

## Complexity

Time `O(n)`, space `O(n)`.

## Worked example

This is the worked example published in the article, replayed by the test suite on every run. The output cannot drift.

### Input

`input`:

```json
{
  "timestamps": [
    "2025-01-01T00:00:00Z",
    "2025-01-02T00:00:00Z",
    "2025-01-03T00:00:00Z",
    "2025-01-04T00:00:00Z",
    "2025-01-05T00:00:00Z",
    "2025-01-06T00:00:00Z"
  ],
  "values": [100, 102, 101, 104, 106, 105],
  "lag": 1,
  "window": 3,
  "resampleSize": 2,
  "period": 3,
  "stationarityTolerance": 3,
  "alpha": 0.4,
  "splitIndex": 4
}
```

### Call

```ts
timeOrderFrequencyRegularityAndFinancialCalendars(input)
```

### Returns

object with 2 fields: ordered, regular

```json
{
  "ordered": true,
  "regular": true
}
```

## Verification and provenance

Tier: **verified** (via input-expected).

The worked example below is the figure published in this algorithm's article, replayed and asserted by the test suite on every build. The arithmetic cannot drift without the build failing.

Both tiers guarantee the signature. Full explanation: https://docs.thefintechbuilder.com/guides/verification/

Generated from the docs.json payload shipped inside fintech-algorithms@0.13.0.
The signature and parameter list are checked against the compiled implementation at build time,
so a description that contradicts the code fails the build rather than reaching this file.

## Links

- Article (how it works, step by step): https://thefintechbuilder.com/foundations/financial-time-series-foundations/time-order-frequency-regularity-and-financial-calendars/
- Implementation source: https://github.com/IslamBaraka90/Fintech-Algorithms-Library/blob/main/src/foundations/financial-time-series-foundations/time-order-frequency-regularity-and-financial-calendars/impl.ts
- Package on npm: https://www.npmjs.com/package/fintech-algorithms
- Domain index for agents: https://docs.thefintechbuilder.com/foundations/llms.txt