Altman Z-Score

Install and import#

bash

npm install fintech-algorithms

import { altmanZScore } from "fintech-algorithms/fundamental-analysis-and-valuation/quality-and-distress/altman-z-score";

Signature#

altmanZScore(data)

Computes the original 1968 five-factor Altman Z-Score for a public manufacturer, weighting working capital, retained earnings, EBIT and sales against total assets and market equity against total liabilities, and places the result in the distress, grey or safe zone.

Parameters#

Name	Type	Notes
`data`	`{ total_assets: number; total_liabilities: number; working_capital: number; retained_earnings: number; ebit: number; market_value_equity: number; sales: number }`	One point-in-time accounting record. The function reads `total_assets` and `total_liabilities` as the two denominators, and `working_capital`, `retained_earnings`, `ebit`, `market_value_equity` and `sales` as the five numerators.

Returns#

{ state: string; method: string; ratios: { working_capital_to_assets: number; retained_earnings_to_assets: number; ebit_to_assets: number; market_equity_to_liabilities: number; sales_to_assets: number }; contributions: { working_capital: number; retained_earnings: number; ebit: number; market_equity: number; sales: number }; z_score: number; zone: string; threshold_policy: string }

ratios holds the five raw ratios and contributions the same ratios after the 1.2, 1.4, 3.3, 0.6 and 1.0 coefficients. z_score is their sum. zone is distress-zone below 1.81, safe-zone above 2.99 and grey-zone between; threshold_policy restates those cutoffs, method is altman-1968-public-manufacturer and state is calculated.

Errors#

When data is not a plain object — throws TypeError
When any field read is missing or not a finite number — throws TypeError
When total_assets or total_liabilities is zero or negative — throws RangeError
When market_value_equity is negative — throws RangeError

Complexity: time O(1), space O(1).

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#

data

{
  "working_capital": 200,
  "retained_earnings": 300,
  "ebit": 160,
  "market_value_equity": 700,
  "total_liabilities": 500,
  "sales": 1200,
  "total_assets": 1000
}

Call#

altmanZScore(data)

Returns#

object with 7 fields: state, method, ratios, contributions, z_score, zone, threshold_policy

{
  "state": "calculated",
  "method": "altman-1968-public-manufacturer",
  "ratios": {
    "working_capital_to_assets": 0.2,
    "retained_earnings_to_assets": 0.3,
    "ebit_to_assets": 0.16,
    "market_equity_to_liabilities": 1.4,
    "sales_to_assets": 1.2
  },
  "contributions": {
    "working_capital": 0.24,
    "retained_earnings": 0.42,
    "ebit": 0.528,
    "market_equity": 0.84,
    "sales": 1.2
  },
  "z_score": 3.2279999999999998,
  "zone": "safe-zone",
  "threshold_policy": "distress<1.81; grey=1.81..2.99; safe>2.99"
}

Other exports#

This module also exports calculate, piotroskiFScore, beneishMScore, sloanAccrualMeasure, ohlsonOScore, zmijewskiXScore, springateSScore, tafflerZScore, fulmerHScore, groverGScore, dechowFScoreForMisstatementRisk, dechowDichevAccrualQuality, modifiedJonesDiscretionaryAccrualModel. Every module additionally exports run as an alias of its primary function, and a meta object carrying its catalog id, domain, family, shape and article URL.