# Sloan Accrual Measure

`D18-F04-A04` · Fundamental Analysis and Valuation → Quality and Distress · archetype `record-transform` · difficulty 2/5 · verification **verified**

Full page: https://docs.thefintechbuilder.com/fundamental-analysis-and-valuation/quality-and-distress/sloan-accrual-measure/
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 { sloanAccrualMeasure } from "fintech-algorithms/fundamental-analysis-and-valuation/quality-and-distress/sloan-accrual-measure";
```

## Signature

```ts
sloanAccrualMeasure(data)
```

Computes Sloan's balance-sheet accrual measure as the change in non-cash working capital less the change in current debt and taxes payable, less depreciation and amortisation, all scaled by average total assets.

## Parameters

| Name | Type | Required | Notes |
| --- | --- | --- | --- |
| `data` | `{ current_assets: number; prior_current_assets: number; cash: number; prior_cash: number; current_liabilities: number; prior_current_liabilities: number; short_term_debt: number; prior_short_term_debt: number; taxes_payable: number; prior_taxes_payable: number; depreciation_and_amortization: number; average_total_assets: number }` | yes | Current and prior balance-sheet values plus the flow items. The function differences `current_assets`, `cash`, `current_liabilities`, `short_term_debt` and `taxes_payable` against their `prior_` twins, subtracts `depreciation_and_amortization`, and scales by `average_total_assets`. |

## Returns

`{ state: string; method: string; delta_current_assets: number; delta_cash: number; delta_current_liabilities: number; delta_short_term_debt: number; delta_taxes_payable: number; depreciation_and_amortization: number; accrual_amount: number; accrual_measure: number; absolute_accrual_measure: number; interpretation: string }`

The five `delta_` keys expose each year-over-year change and `depreciation_and_amortization` is echoed back. `accrual_amount` is the unscaled accrual, `accrual_measure` is that amount over average total assets and `absolute_accrual_measure` is its magnitude. `interpretation` is `income-decreasing-accrual` when the measure is negative, `income-increasing-accrual` when positive and `zero-net-accrual` at exactly zero. `method` is `sloan-1996-balance-sheet-accrual` 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 average_total_assets is zero or negative — throws RangeError
- When depreciation_and_amortization is negative — 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
{
  "current_assets": 500,
  "prior_current_assets": 450,
  "cash": 100,
  "prior_cash": 90,
  "current_liabilities": 260,
  "prior_current_liabilities": 240,
  "short_term_debt": 70,
  "prior_short_term_debt": 60,
  "taxes_payable": 20,
  "prior_taxes_payable": 18,
  "depreciation_and_amortization": 60,
  "average_total_assets": 950
}
```

### Call

```ts
sloanAccrualMeasure(data)
```

### Returns

object with 12 fields: state, method, delta_current_assets, delta_cash, delta_current_liabilities, delta_short_term_debt, delta_taxes_payable, depreciation_and_amortization, …

```json
{
  "state": "calculated",
  "method": "sloan-1996-balance-sheet-accrual",
  "delta_current_assets": 50,
  "delta_cash": 10,
  "delta_current_liabilities": 20,
  "delta_short_term_debt": 10,
  "delta_taxes_payable": 2,
  "depreciation_and_amortization": 60,
  "accrual_amount": -28,
  "accrual_measure": -0.029473684210526315,
  "absolute_accrual_measure": 0.029473684210526315,
  "interpretation": "income-decreasing-accrual"
}
```

## Other exports

`calculate`, `altmanZScore`, `piotroskiFScore`, `beneishMScore`, `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.

## 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/sloan-accrual-measure/
- Implementation source: https://github.com/IslamBaraka90/Fintech-Algorithms-Library/blob/main/src/fundamental-analysis-and-valuation/quality-and-distress/sloan-accrual-measure/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