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Purpose

SigmaGrid exists to provide institutional-grade fundamentals for synthetic-equity perpetual markets.

The problem​

Synthetic-equity perps (SPY-PERP, QQQ-PERP, TSLA-PERP, etc.) trade 24/7, cross-venue, and increasingly agent-driven. But unlike listed equities, they typically trade without:

  • a stable institutional fair-value anchor
  • forward-looking volatility forecasts
  • consistent drift estimates
  • regime classification (trend vs chop, high-vol vs low-vol)
  • explicit event calendars and sensitivities

That absence creates structural issues:

  • Cross-venue mispricings persist longer than they should.
  • Directional signals are noisy and fragile.
  • Liquidation cascades cluster around macro events.
  • Funding patterns become unstable.
  • Risk controls for agent-driven execution remain weak.

The SigmaGrid approach​

SigmaGrid rebuilds the institutional fundamentals layer for synthetic-equity perps and exposes it as a machine-readable JSON API.

  • Every supported ticker receives a real-time snapshot of mandatory fields: fair value, volatility forecasts, drift, regime, and macro event context.
  • Optional macro sensitivities (beta_macro, beta_yield, beta_dollar, beta_vol_index) compress complex relationships into a compact, safe-to-expose signal surface.
  • All fields are designed so execution engines, risk systems, and AI agents can plug them directly into routing, sizing, and hedging logic.

The goal is simple: make 24/7 synthetic-equity markets behave more like properly anchored institutional products, without forcing every desk to rebuild decades of fundamentals research.