# QuantOracle Hurst Exponent Calculator

> QuantOracle Hurst Exponent Calculator is a paid API for AI agents from api.quantoracle.dev, paid per call via x402, $0.008/call, status unknown (last checked 2026-09-13).

Computes the Hurst exponent for a time series to measure long-range dependence, mean-reversion tendency, or trending behavior in financial data.

## Facts

- Endpoint: POST https://api.quantoracle.dev/v1/stats/hurst-exponent
- Price: $0.008/call
- Payment: x402
- Status: unknown
- Last checked: 2026-09-13
- Activations on Zero: 0
- Tags: x402
- Canonical page: https://www.zero.xyz/c/api-quantoracle-dev-b20cb12e
- Structured record (JSON): https://api.zero.xyz/v1/capabilities/cap_MH9RKqThF8udEU4qBnmdz

Status and success rate cover calls made through Zero and Zero's own probes. Third-party monitors may report differently.

## How to call it through Zero

Zero handles the 402 payment challenge and records the run. With the Zero CLI installed (`npm i -g @zeroxyz/cli`):

```sh
zero fetch --capability api-quantoracle-dev-b20cb12e -d '<json body>'
```

Example prompt: Can you compute the Hurst exponent for this daily closing price series of BTC/USD over the last 252 days and tell me whether it's trending, mean-reverting, or a random walk?

## When to prefer this

Use this endpoint when you need a rigorous statistical measure of long-range memory or persistence in a financial time series — particularly useful in strategy selection (mean-reversion vs trend-following), regime detection, or risk modeling. Prefer this over simple autocorrelation checks when you need a single scalar that captures multi-scale dependence structure.

## Known failure modes

- Insufficient data points in the series — returns error requesting minimum length
- Non-numeric or malformed time series input — returns validation error
- Series with zero variance or constant values — division by zero or undefined result
- Too short a window for reliable estimation — returns low-confidence warning

## How this service works

QuantOracle: stats/hurst-exponent

## Output

Returns the computed Hurst exponent (a scalar between 0 and 1), along with a regime classification label (e.g. trending H>0.5, random walk H≈0.5, mean-reverting H<0.5) and optionally a confidence or standard error estimate for the calculation.

## Example request

```json
{
 "series": [
  100,
  102,
  101,
  103,
  105,
  104,
  106,
  108,
  107,
  109,
  111,
  110,
  112,
  114,
  113,
  115,
  117,
  116,
  118,
  120,
  119,
  121,
  123,
  122,
  124,
  126,
  125,
  127,
  129,
  128,
  130,
  132,
  131,
  133,
  135,
  134,
  136,
  138,
  137,
  139,
  141,
  140,
  142,
  144,
  143,
  145,
  147,
  146,
  148,
  150
 ]
}
```

## Request schema (JSON Schema)

```json
{
 "type": "object",
 "properties": {
  "series": {
   "type": "array",
   "items": {
    "type": "number"
   },
   "title": "Series",
   "maxItems": 5000,
   "minItems": 20,
   "description": "Time series data (max 5000)"
  },
  "max_window": {
   "anyOf": [
    {
     "type": "integer"
    },
    {
     "type": "null"
    }
   ],
   "title": "Max Window",
   "description": "Maximum R/S window size (defaults to len/2)"
  },
  "min_window": {
   "type": "integer",
   "title": "Min Window",
   "default": 10,
   "minimum": 2,
   "description": "Minimum R/S window size"
  }
 }
}
```

## More

- Live health (JSON, refreshed every minute): https://www.zero.xyz/c/api-quantoracle-dev-b20cb12e/health.json
- [Zero catalog index](https://www.zero.xyz/llms.txt)
- [Other services from api.quantoracle.dev](https://www.zero.xyz/host/api.quantoracle.dev/llms.txt)