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ADH US Mega-Cap Stock Signals
x402
ADH US Mega-Cap Stock Signals is a paid API for AI agents from agentdatum.com, paid per call via x402, $0.05/call, status unknown (last checked 2026-09-15).
Returns momentum, volatility, z-score, and percentile-rank signals for US mega-cap equities (e.g. AAPL) derived from time-series data across 239 sources.
Price / call$0.05
Success—
StatusUnknown
How this service works
US Mega-Cap Signals — Momentum, volatility, z-score, and percentile signals for 10 US mega-caps like Apple, Microsoft, Nvidia, Tesla, with 30-day trends.
Output
Returns a JSON object containing per-ticker signal objects for US mega-cap equities. Each signal includes: 1-day log return (ret_1), 4-period momentum (mom_4), 20-day volatility (vol_20), 10- and 30-day z-scores, 10- and 30-day percentile ranks, last price, data point count, status, and a timestamped price history array. Also includes metadata: product label, data source, data type, and generation timestamp.
Example use cases
Momentum screening for large-cap stocks
“Give me the current momentum and percentile rank signals for US mega-cap equities — I want to know which ones are showing strong 4-period momentum and whether they're in the top or bottom half of their 30-day range.”
Volatility regime check before earnings
“What's the current 20-day realized volatility and z-score for mega-cap US stocks right now? I need to know if volatility is elevated versus historical norms before I size my positions.”
Automated signal injection for AI trading agent
“Fetch the latest ADH mega-cap signals including log returns, z-scores, and percentile ranks so my trading agent can assess whether AAPL and peers are in a mean-reversion or trend-continuation regime.”
Technical details
Endpoint
GEThttps://agentdatum.com/api/v1/d/sig-us-mega-capWhen to prefer
Choose this endpoint when you need pre-computed, statistically derived signals (momentum, volatility, z-score, percentile rank) for US mega-cap equities ready to inject into an AI context — especially when you want entity-resolved, time-synchronized intelligence rather than raw price feeds. Prefer this over raw market data APIs when you need derived quantitative metrics (z-scores, percentile ranks) already computed across a 239-source data library, and when you want agent-native x402 micropayment settlement.
Side effects
- Payment not received — x402 payment required before data is served
- Stale data — generated_at timestamp may lag real-time by minutes or hours
- Empty or partial signals array if upstream data sources are unavailable
- Rate limiting if payment is not settled per-call via x402
- Schema mismatch if response format changes between API versions
Input
Schema · Request body
| Field | Type | Description |
|---|---|---|
| inputrequired | object | |
| output | object |
Output
Schema · Response
{
"type": "json",
"example": {
"raw": {
"method": "x402 signals: log-return momentum / volatility / z-score / percentile rank over time-series library",
"product": "美股巨头信号",
"signals": [
{
"mom_4": 0.032139,
"ret_1": 0.00294,
"points": 257,
"series": "stock-quote__AAPL",
"status": "ok",
"vol_20": 0.02298,
"history": [
{
"ts": 1782480600,
"value": 283.779999
},
{
"ts": 1782480600,
"value": 283.779999
}
],
"zscore_10": -0.6696,
"zscore_30": -0.1112,
"last_value": 313.33,
"pctrank_10": 50,
"pctrank_30": 43.3
},
{
"mom_4": 0.032139,
"ret_1": 0.00294,
"points": 257,
"series": "stock-quote__AAPL",
"status": "ok",
"vol_20": 0.02298,
"history": [
{
"ts": 1782480600,
"value": 283.779999
},
{
"ts": 1782480600,
"value": 283.779999
}
],
"zscore_10": -0.6696,
"zscore_30": -0.1112,
"last_value": 313.33,
"pctrank_10": 50,
"pctrank_30": 43.3
}
],
"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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