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ADH Signal Space — Space Weather Financial Signals
x402
ADH Signal Space — Space Weather Financial Signals is a paid API for AI agents from agentdatum.com, paid per call via x402, $0.01/call, status unknown (last checked 2026-10-20).
Returns quantitative signal indicators (momentum, volatility, z-score, percentile rank) for space weather (Kp index) time-series data, processed from raw sources into agent-ready financial intelligence.
Price / call$0.01
Success—
StatusUnknown
How this service works
ADH 金融情报层：把 239 个原始数据源洗成带实体解析、时间同步、溯源与派生结论的情报（宏观regime / 加密尽调 / 事件窗口），免费注入你的 AI 上下文。Agent 走 x402 结算，人类订阅（PayPal）即将上线。
Output
A JSON object containing the spaceweather-kp signal series with: log-return momentum (mom_4, ret_1), 20-period volatility (vol_20), 10- and 30-period z-scores, 10- and 30-period percentile ranks, last observed value, number of data points, status, a history array of {ts, value} pairs, and a generation timestamp. Wrapped with source, data_type, and collected_at metadata fields.
Example use cases
Macro regime geomagnetic anomaly check
“Fetch the current space weather Kp index signal from ADH and tell me if it's statistically anomalous — I need the z-score and percentile rank to decide whether to flag it in my macro regime model.”
Algo trading space weather factor
“Get me the latest ADH sig-space signal metrics — momentum over 4 periods, 20-period volatility, and the 10-period percentile rank for the spaceweather-kp series — so I can incorporate it as a factor in my quant model.”
Event window space weather monitoring
“Check the ADH signal space data for space weather right now and show me the last value, its z-score, and recent history timestamps — I'm tracking whether a geomagnetic event is developing that might affect my positions.”
Technical details
Endpoint
GEThttps://agentdatum.com/api/v1/d/sig-space?utm_source=zero.xyzWhen to prefer
Choose this endpoint when you need pre-computed quantitative signal metrics (momentum, volatility, z-score, percentile rank) derived from space weather (Kp index) time-series data specifically, without building your own data pipeline. Prefer it over raw space weather APIs when you want agent-ready, normalized financial intelligence with provenance metadata and no need for your own time-series library. Best suited for quant models, macro regime monitoring, or event-window analysis that incorporates geomagnetic factors.
Side effects
- Payment not settled via x402 — returns 402 Payment Required if USDC payment of $0.01 is not included
- Insufficient historical data — z-score and percentile rank for 30-period window may return null if series is too short
- Upstream data source unavailable — signal status field may indicate error instead of 'ok'
- Stale data — generated_at timestamp may lag real-time if source feed is delayed
Output
Schema · Response
{
"type": "json",
"example": {
"raw": {
"method": "x402 signals: log-return momentum / volatility / z-score / percentile rank over time-series library",
"product": "太空天气信号",
"signals": [
{
"mom_4": -0.512824,
"ret_1": -0.285179,
"points": 24,
"series": "spaceweather-kp",
"status": "ok",
"vol_20": 0.538968,
"history": [
{
"ts": 1785218400,
"value": 1.67
},
{
"ts": 1785218400,
"value": 1.67
}
],
"zscore_10": -0.642,
"zscore_30": null,
"last_value": 1,
"pctrank_10": 20,
"pctrank_30": null
}
],
"generated_at": "2026-08-14T00:22:02Z"
},
"source": "datum-signals",
"data_type": "信号指标",
"collected_at": "2026-08-14T00:22:02Z"
}
}Tags
x402
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