fintech-algorithms
Using a coding agent? Give it the skill: npx skills add IslamBaraka90/Fintech-Algorithms-Library What it does →

Liquidity Screen

Install and import#

bash
npm install fintech-algorithms
ts
import { calculate } from "fintech-algorithms/index-and-benchmark-engineering/governance-and-maintenance/liquidity-screen";

Signature#

calculate(data)

Requires sustained tradability, not a single good month. Median turnover over a minimum number of months is the standard test, and the median is deliberate: a mean is dominated by one spike of activity.

Parameters#

NameTypeNotes
data{ records: Record[]; minimumMedianTurnover: number; minimumMonths: number }minimumMonths is the sustained-history requirement, which is what stops a newly listed name qualifying on a burst of IPO volume.

Returns#

{ results, passingIds, threshold }

Per-candidate results with the realised median and the threshold applied.

Errors#

  • When minimumMonths is less than 1 — throws

Complexity: time O(n × months), space O(n).

Worked example#

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

Input#

data
{
  "records": [
    {
      "id": "A",
      "monthlyTurnover": [0.18, 0.21, 0.2, 0.17, 0.23, 0.19]
    },
    {
      "id": "B",
      "monthlyTurnover": [0.04, 0.06, 0.05, 0.03, 0.05, 0.04]
    },
    {
      "id": "C",
      "monthlyTurnover": [0.12, 0.11, 0.14, 0.1, 0.13, 0.12]
    }
  ],
  "minimumMedianTurnover": 0.08,
  "minimumMonths": 6
}

Call#

calculate(data)

Returns#

object with 3 fields: results, passingIds, threshold

{
  "results": [
    {
      "id": "A",
      "medianTurnover": 0.195,
      "passes": true
    },
    {
      "id": "B",
      "medianTurnover": 0.045,
      "passes": false
    },
    {
      "id": "C",
      "medianTurnover": 0.12,
      "passes": true
    }
  ],
  "passingIds": ["A", "C", "D"],
  "threshold": 0.08
}

Diagrams#

Liquidity Screen — article hero
Liquidity Screen — failure guard
Liquidity Screen — worked example

Calculation flow#

Liquidity Screen calculation flow
flowchart LR
    A["Point-in-time inputs"] --> B["Validate units and timing"]
    B --> C{"Contract feasible?"}
    C -->|No| D["Reject with reason"]
    C -->|Yes| E["Calculate Liquidity Screen"]
    E --> F["Recompute invariants"]
    F --> G{"Checks pass?"}
    G -->|No| D
    G -->|Yes| H["Publish audited output"]
Liquidity Screen methodology state
stateDiagram-v2
    [*] --> FrozenInputs
    FrozenInputs --> Validated: contract passes
    FrozenInputs --> Rejected: missing or infeasible
    Validated --> Calculated: apply named rule
    Calculated --> Audited: invariants pass
    Calculated --> Rejected: invariant fails
    Audited --> Published: version and timestamp recorded
    Published --> Revised: approved correction
    Revised --> FrozenInputs: rebuild from retained source state

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.

Read the article →

References#

The rest of the Governance and Maintenance family#