# Fulmer H-Score

`D18-F04-A09` · Fundamental Analysis and Valuation → Quality and Distress · archetype `record-transform` · difficulty 3/5 · verification **verified**

Full page: https://docs.thefintechbuilder.com/fundamental-analysis-and-valuation/quality-and-distress/fulmer-h-score/
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 { fulmerHScore } from "fintech-algorithms/fundamental-analysis-and-valuation/quality-and-distress/fulmer-h-score";
```

## Signature

```ts
fulmerHScore(data)
```

Computes Fulmer's 1984 nine-factor small-firm H-Score, including the two base-10 logarithm terms on tangible assets and interest coverage, and reports which side of the zero cutoff the score falls on.

## Parameters

| Name | Type | Required | Notes |
| --- | --- | --- | --- |
| `data` | `{ total_assets: number; total_debt: number; equity: number; interest_expense: number; tangible_assets_usd_thousands: number; ebit: number; retained_earnings: number; sales: number; ebt: number; operating_cash_flow: number; current_liabilities: number; working_capital: number }` | yes | One accounting record. `total_assets` scales `retained_earnings`, `sales`, `total_debt` and `current_liabilities`; `equity` scales `ebt`; `total_debt` scales `operating_cash_flow` and `working_capital`. `tangible_assets_usd_thousands` must already be stated in USD thousands because it is passed straight to a base-10 logarithm, and `ebit` over `interest_expense` supplies the second logarithm. |

## Returns

`{ state: string; method: string; variables: { retained_earnings_to_assets: number; sales_to_assets: number; ebt_to_equity: number; operating_cash_flow_to_debt: number; debt_to_assets: number; current_liabilities_to_assets: number; log10_tangible_assets_usd_thousands: number; working_capital_to_debt: number; log10_ebit_interest: number }; h_score: number; screen: string; index_cutoff: number; scale_policy: string }`

`variables` holds the nine factors and `h_score` weights them by 5.528, 0.212, 0.073, 1.270, -0.120, 2.335, 0.575, 1.083 and 0.894 before subtracting the constant 6.075. `index_cutoff` is 0 and `screen` is `distress-side` for a negative score and `non-distress-side` otherwise. `scale_policy` records that tangible assets are expressed in USD thousands before the logarithm. `method` is `fulmer-1984-small-firm-nine-factor` 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, total_debt, equity, interest_expense or tangible_assets_usd_thousands is zero or negative — throws RangeError
- When ebit divided by interest_expense is zero or negative, so the base-10 logarithm is undefined — throws RangeError

## Complexity

Time `O(1)`, space `O(1)`.

## Worked example

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`:

```json
{
  "total_assets": 1000,
  "total_debt": 550,
  "equity": 450,
  "interest_expense": 40,
  "tangible_assets_usd_thousands": 800000,
  "ebit": 160,
  "retained_earnings": 300,
  "sales": 1200,
  "ebt": 140,
  "operating_cash_flow": 110,
  "current_liabilities": 250,
  "working_capital": 200
}
```

### Call

```ts
fulmerHScore(data)
```

### Returns

object with 7 fields: state, method, variables, h_score, screen, index_cutoff, scale_policy

```json
{
  "state": "calculated",
  "method": "fulmer-1984-small-firm-nine-factor",
  "variables": {
    "retained_earnings_to_assets": 0.3,
    "sales_to_assets": 1.2,
    "ebt_to_equity": 0.3111111111111111,
    "operating_cash_flow_to_debt": 0.2,
    "debt_to_assets": 0.55,
    "current_liabilities_to_assets": 0.25,
    "log10_tangible_assets_usd_thousands": 5.903089986991944,
    "working_capital_to_debt": 0.36363636363636365,
    "log10_ebit_interest": 0.6020599913279624
  },
  "h_score": 0.958597667696858,
  "screen": "non-distress-side",
  "index_cutoff": 0,
  "scale_policy": "tangible assets expressed in USD thousands before log10"
}
```

## Other exports

`calculate`, `altmanZScore`, `piotroskiFScore`, `beneishMScore`, `sloanAccrualMeasure`, `ohlsonOScore`, `zmijewskiXScore`, `springateSScore`, `tafflerZScore`, `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.

## Verification and provenance

Tier: **verified** (via D).

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/fundamental-analysis-and-valuation/quality-and-distress/fulmer-h-score/
- Implementation source: https://github.com/IslamBaraka90/Fintech-Algorithms-Library/blob/main/src/fundamental-analysis-and-valuation/quality-and-distress/fulmer-h-score/impl.ts
- Package on npm: https://www.npmjs.com/package/fintech-algorithms
- Domain index for agents: https://docs.thefintechbuilder.com/fundamental-analysis-and-valuation/llms.txt