quality¶

GET https://api.hypquant.com/v1/quality

Returns the Data Quality Score (DQS) for a symbol, with per-component breakdown. Requires an API key.

Parameters¶

Name	Type	Required	Description
`symbol`	string	yes	Trading pair, e.g. `BTC-USDC`
`exchange`	string	yes	`hyperliquid` or `binance`
`timeframe`	string	no	Filter to one timeframe. Returns all available timeframes if omitted

Response¶

{
  "exchange": "hyperliquid",
  "symbol": "BTC-USDC",
  "timeframes": {
    "1h": {
      "dqs": "0.972000",
      "computed_at": "2024-06-01T12:00:00+00:00",
      "components": {
        "gap_rate_score": "0.998000",
        "anomaly_score": "0.980000",
        "consistency_score": "0.960000",
        "freshness_score": "0.950000"
      }
    },
    "4h": {
      "dqs": "0.985000",
      "computed_at": "2024-06-01T12:00:00+00:00",
      "components": {
        "gap_rate_score": "0.999000",
        "anomaly_score": "0.990000",
        "consistency_score": "0.960000",
        "freshness_score": "0.990000"
      }
    }
  }
}

Timeframes are returned only for granularities allowed by the caller's tier. Free tier callers will see 1h, 4h, 1d.

DQS formula¶

DQS = 0.30 × gap_rate_score
    + 0.25 × anomaly_score
    + 0.25 × consistency_score
    + 0.20 × freshness_score

Component	Formula
`gap_rate_score`	`present_candles / expected_candles` over the last 7 days
`anomaly_score`	`1 − (candles_with_zscore_gt_4 / total_candles)`
`consistency_score`	`1` if avg basis < 0.5%, otherwise decays linearly to `0` at 2%
`freshness_score`	`1` if latest candle is within SLA, otherwise `0`

Freshness SLA by timeframe¶

Timeframe	SLA
1m	5 minutes
5m	15 minutes
15m	30 minutes
1h	90 minutes
4h	6 hours
1d	26 hours

Interpreting DQS¶

Range	Interpretation
0.95 – 1.00	Production-ready
0.85 – 0.95	Minor issues — check the component scores
0.70 – 0.85	Data quality concerns — backtest results may be affected
< 0.70	Significant issues — do not use for production strategies

Examples¶

Python SDKcurl

from hypquant import MarketData

with MarketData(api_key="qp_...") as md:
    # All timeframes
    quality = md.quality("BTC-USDC", exchange="hyperliquid")
    for tf, dqs in quality["timeframes"].items():
        print(f"{tf}: {dqs['dqs']}")

    # Specific timeframe
    quality = md.quality("BTC-USDC", exchange="hyperliquid", timeframe="1h")

curl -H "X-API-Key: qp_..." \
  "https://api.hypquant.com/v1/quality?symbol=BTC-USDC&exchange=hyperliquid"

Error responses¶

HTTP	`error` code	Cause
401	`UNAUTHORIZED`	Missing or invalid API key
403	`TIER_LIMIT_EXCEEDED`	Requested timeframe not available on current plan
404	`QUALITY_NOT_FOUND`	No quality data computed yet for this symbol/timeframe
429	`RATE_LIMIT_EXCEEDED`	Daily or per-minute request quota reached