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For Agents & Automated Systems

SigmaGrid is designed to be consumed by agents, bots, and automated execution systems, not just humans.

Public docs live now — Paid API launching Q1 2026
Base API URL (when live): https://api.sigmagrid.app

Core ideas for agents​

1. Use /signals/{ticker} as your primary surface​

The /signals/{ticker} endpoint gives you a consolidated view, including:

  • Core mandatory fields:

    • timestamp, ticker, fair_value, vol_forecast_1h, vol_forecast_4h, regime, drift_1h, drift_overnight, event_next, event_impact, event_bias

  • Extended signal fields:

    • fv_upper, fv_lower, premiums, z_score, reversion_prob, shock_index

  • Optional macro sensitivities:

    • beta_macro, beta_yield, beta_dollar, beta_vol_index

Use this for routing, sizing, and hedging decisions.

2. Example agent decision loop (pseudo-code)​

loop every 60 seconds:

  sig = GET /signals/SPY

  # Safety: regime + events
  if sig.regime == "HVOL" and sig.event_impact in ["high", "extreme"]:
      reduce_position_size()
      if sig.event_bias == "risk-off":
          close_risk_on_positions()

  # Directional trades
  if sig.drift_1h > 0 and sig.z_score < 1.0:
      open_or_add_long(size = base_size * (1 + sig.drift_1h))

  elif sig.reversion_prob > 0.75 and sig.z_score > 1.5:
      open_mean_reversion_short(size = base_size * sig.reversion_prob)

  # Macro-aware sizing
  macro_intensity = abs(sig.beta_macro) + abs(sig.beta_vol_index)
  if macro_intensity > 1.5:
      apply_leverage_cap()

3. How to interpret key fields​

  • fair_value, fv_upper, fv_lower

    Treat as the institutional anchor for the perp.

    • Price above fv_upper + high reversion_prob → mean-reversion setup.
    • Price below fv_lower + positive drift_1h → trend-continuation setup.

  • regime & shock_index

    Use as risk multipliers:

    • trend + low shock_index → you can size more aggressively.
    • HVOL + high shock_index → tighten stops, reduce leverage, or pause.

  • event_next, event_impact, event_bias

    Use to modify behaviour around macro events:

    • event_impact: extreme → shrink risk window before and after the event.
    • event_bias: risk-off → avoid opening new risk-on positions.

  • Macro betas (beta_macro, beta_yield, beta_dollar, beta_vol_index)

    Use them as overlay controls, not raw trading signals:

    • Large beta_yield in a hawkish environment → favour short exposure.
    • Large beta_vol_index → automatic volatility-aware position caps.

4. Consumption model (Q1 2026 and beyond)​

When live, each request to https://api.sigmagrid.app will be:

  • paid per request in stablecoins via x402 + thirdweb Nexus Gateway, and
  • authorised at the protocol level (no long-lived API keys).

Agents should be prepared to:

  1. Construct the HTTP call to the relevant endpoint (e.g. /signals/SPY), and
  2. Wrap it in the required x402 payment flow once published.

Until launch, the docs, OpenAPI spec, llms.txt, and mcp.json provide a stable contract for integration.