S&P 500 (SPY)
Top drivers
⌁ mcp.call("adw-104") vADW-104-live-1.0 Helps traders identify assets with expanding volatility ranges to anticipate breakout opportunities and optimize entry timing.
S&P 500 (SPY)
Top drivers
⌁ mcp.call("adw-104") vADW-104-live-1.0 A breakout-detection agent scans the ADW-104 IOM each morning; when price_range_ratio (ATR-14 / ATR-252 baseline) exceeds 1.0 and the score is above 85 — the current reading is 91.9, at the 90th percentile of a 2,499-day history — it automatically generates entry-candidate alerts for momentum strategies and widens the bid-ask spread on the market-making side of the book to account for elevated intraday range risk. Source_lineage certifying the Stooq daily OHLCV input and methodology_version locking the True-Range pipeline let the compliance team verify the signal's data provenance in post-trade surveillance.
A head of quantitative research uses ADW-104 to screen a multi-asset portfolio for assets whose near-term range is expanding well above the one-year baseline before committing to breakout trend-following positions. The current 91.9 score — near the top decile of all readings since July 2016 — tells the researcher that the SPY ATR-14 is running roughly 1.5x its 252-day baseline, a level historically associated with sustained directional moves rather than mean-reverting chop, allowing the team to justify wider profit targets and looser trailing stops without a custom vol-surface build.
True Range per bar → ATR-14 / ATR-252 ratio → percentile-rank vs rolling history → 0-100 score; >1 = range expanding vs baseline
Version ADW-104-live-1.0 · validated to beat a naive baseline · benchmark: none
One call returns the answer with its reasoning attached — the live Intelligence Object for ADW-104.
{
"product_id": "ADW-104",
"entity": "S&P 500 (SPY)",
"score": 91.9,
"trend": "expanding",
"confidence": 0.8,
"top_drivers": [
{
"factor": "atr_14d_vs_252d_ratio",
"contribution": 1.5381
},
{
"factor": "atr_14d",
"contribution": 11.3236
},
{
"factor": "atr_252d_baseline",
"contribution": 7.3618
}
],
"recommended_use": "Identify expanding volatility ranges to time breakout entries. Score > 65 = range expansion vs historical baseline.",
"methodology_version": "ADW-104-live-1.0",
"freshness": "2026-06-26T20:00:16.189Z",
"coverage": "S&P 500 ETF daily OHLCV — 252 days",
"source_lineage": [
"Stooq daily OHLCV (SPY)"
],
"allowed_use": "informational",
"atr_14d": 11.3236,
"atr_252d_baseline": 7.3618,
"price_range_ratio": 1.5381,
"range_regime": "expanding",
"validation_status": "descriptive"
} Every product conforms to the Intelligence Object Model — typed, versioned, and discoverable.
Dashboard
Read the score + drivers in the console.
REST API
/v1/intelligence/adw-104
MCP tool
adw.adw_104
Marketplace
Discoverable by any MCP agent via the MCP registry.
White-label
Embed under your own brand (Platinum).
Enables traders to anticipate imminent volatility regime shifts to optimize position sizing and hedge timing before market instability occurs.
Method: Log-returns → 60-day rolling z-score → CUSUM(k=0.5) → Shannon entropy weight → sigmoid-normalize over 252-day history → 0-100 score
Enables traders to detect early-stage increases in fat-tail risk to prevent catastrophic drawdowns during market stress events.
Method: 252-day baseline σ → threshold T=1.5σ → P_base + P_recent (20-day) tail exceedance rates → Shift = P_recent−P_base → sigmoid → 0-100
Identify cyclical volatility regime shifts to time entries and exits with higher predictive accuracy than standard volatility metrics.
Method: 20-day rolling realized vol series → 10-day OLS slope → percentile-rank over 252-day slope history → 0-100 score