Tier 2Flagship
Macro Lead
Lead-lag correlation matrix across 17 axes with 4-state regime overlay. Calculated alpha, not raw data — delivered as a single API call.
$2,500 / month
What you get
Three signal layers, one endpoint.
Lead-lag matrix
17 macro axes (DXY, ES, NQ, BTC, ETH, GLD, TLT, HYG, etc.) cross-correlation grid. 1-minute resolution. 1-year history. Updated on every tick.
Regime overlay
4-state Non-homogeneous Hidden Markov Model (NHMM) classifier. Current state probability + 24h transition probability.
Monthly research PDF
20-page analyst report with regime context, factor crowding, and tactical positioning notes.
Sample response
GET /v1/correlation/matrix
{
"matrix": {
"as_of": "2026-05-04T08:00:00Z",
"axes": ["DXY", "ES", "NQ", "BTC", "ETH", "GLD", "TLT", "HYG", "..."],
"n_axes": 17,
"lead_lag_grid": [
[0.00, 0.42, 0.38, 0.21, 0.18, -0.05, -0.31, 0.27],
[0.42, 0.00, 0.91, 0.34, 0.31, 0.08, -0.45, 0.51],
[0.38, 0.91, 0.00, 0.32, 0.30, 0.07, -0.43, 0.48]
],
"regime_overlay": {
"current_state": "risk_on",
"probability": 0.73,
"transition_prob_24h": 0.18
}
}
}How to call
Two lines of code.
curl
curl -H "Authorization: Bearer $ATHENA_DATA_API_KEY" \ "https://api.athena-data.com/v1/correlation/matrix?window=1d&axes=all"
Python
import os, requests
key = os.environ["ATHENA_DATA_API_KEY"]
r = requests.get(
"https://api.athena-data.com/v1/correlation/matrix",
params={"window": "1d", "axes": "all"},
headers={"Authorization": f"Bearer {key}"},
)
matrix = r.json()["matrix"]
print(matrix["regime_overlay"]["current_state"]) # "risk_on"Full endpoint reference at /docs/endpoints. SDKs for Python and TypeScript ship with subscription.
SLA
Uptime
99.5%
p99 latency
< 300ms
Update cadence
Tick-driven