# Drawdown and Maximum Drawdown

`D00-F11-A03` · Financial Mathematics, Statistics, and Data Foundations → Financial Risk and Performance Statistics · archetype `record-transform` · difficulty 1/5 · verification **verified**

Full page: https://docs.thefintechbuilder.com/foundations/financial-risk-and-performance-statistics/drawdown-and-maximum-drawdown/
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 { drawdownAndMaximumDrawdown } from "fintech-algorithms/foundations/financial-risk-and-performance-statistics/drawdown-and-maximum-drawdown";
```

## Signature

```ts
drawdownAndMaximumDrawdown(input)
```

Compounds a return series into a wealth path and tracks how far that path sits below its own running peak.

## Parameters

| Name | Type | Required | Notes |
| --- | --- | --- | --- |
| `input` | `D00Input` | yes | Reads `returns` and `benchmark`, two aligned non-empty lists of finite periodic returns, and `frequency`, the number of periods per year. The wealth path is built from `returns` alone. |

## Returns

`D00Output`

`drawdowns` gives one non-positive figure per period, each the fractional shortfall against the running peak. `maximumDrawdown` is the most negative of them and `endingWealth` is the final value of a path that starts at one.

## Errors

- When `returns` or `benchmark` is absent, empty, or holds a non-finite number — throws RangeError
- When `returns` and `benchmark` differ in length, or hold fewer than two observations — throws RangeError
- When `frequency` is zero or negative — 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
{
  "returns": [0.01, -0.02, 0.015, -0.01, 0.03],
  "benchmark": [0.008, -0.01, 0.012, -0.006, 0.02],
  "frequency": 252,
  "target": 0,
  "confidence": 0.8,
  "riskFree": 0.0001,
  "weights": [0.6, 0.4],
  "covarianceMatrix": [
    [0.04, 0.01],
    [0.01, 0.09]
  ]
}
```

### Call

```ts
drawdownAndMaximumDrawdown(input)
```

### Returns

object with 2 fields: drawdowns, maximumDrawdown

```json
{
  "drawdowns": [0, -0.020000000000000018, -0.0053000000000001934, -0.015247000000000233, 0],
  "maximumDrawdown": -0.020000000000000018
}
```

## 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-risk-and-performance-statistics/drawdown-and-maximum-drawdown/
- Implementation source: https://github.com/IslamBaraka90/Fintech-Algorithms-Library/blob/main/src/foundations/financial-risk-and-performance-statistics/drawdown-and-maximum-drawdown/impl.ts
- Package on npm: https://www.npmjs.com/package/fintech-algorithms
- Domain index for agents: https://docs.thefintechbuilder.com/foundations/llms.txt