/macro-event-calendar

name: macro-event-calendar
description: Forward calendar of the macro releases that reprice the whole book (FOMC, CPI, PPI, NFP, ISM manufacturing/services, GDP, PCE, JOLTS, jobless claims, retail sales, Consumer Confidence, Michigan Sentiment). Each event ships with release date/time, an impact tier, and the historical mean absolute 1-day SPY move on that release type. Sibling to earnings-blackout: earnings-blackout is single-name and this is macro-level. Use when running a portfolio review, sizing around a print, or answering "what's on the calendar this month."

macro-event-calendar

You hand over a forward window (default 30 days) and get back the macro release schedule with historical reaction stats per event type.

Sibling to earnings-blackout. earnings-blackout covers single-name prints; this covers the macro releases that move the whole tape. Every portfolio review should run both.

When to invoke

• Portfolio review workflow: after earnings-blackout, run this for

the macro-side of the calendar

• Pre-trade planning: "what's the next FOMC / CPI / NFP" before

sizing a position

• The user says "macro calendar", "FOMC when", "CPI print", "what

data is out this week"

What you need

• `MASSIVE_API_KEY` for SPY historical reactions (Stocks Basic is

enough; the tool is one range aggs call for SPY over the history window)

What you get back

**Layer 1 JSON** matching [`output-schema.json`](./output-schema.json). Per-event: date, release time ET, impact tier, historical mean / median / p90 |1-day SPY move|, sample size. Plus a `crowded_days` block flagging dates with 2+ events.

**Layer 2 rendered table** sorted by date. Impact tier rendered as 1-4 stars. Pattern-derived dates marked with `~` so users know to verify against the official calendar. See [`references/rendering.md`](./references/rendering.md).

How it works

1. **Generate scheduled dates** for each event type over the forward window via pattern rules (NFP = 1st Friday, CPI = 2nd Wednesday, ISM Mfg = 1st business day, etc.). FOMC dates are hardcoded from the official published schedule. 2. **Fetch SPY history** for the `history_days` lookback (default 730 = 2 years). 3. **For each event type, compute historical stats**: generate the same pattern dates over history, look up SPY's |1-day move| on each matched date, aggregate to mean / median / p90. 4. **Flag crowded days** where 2+ events land on the same date.

Endpoints used

• `GET /v2/aggs/ticker/SPY/range/1/day/{from}/{to}` (one call for

the history window)

Doesn't handle (yet)

• **No prior / consensus values.** Add via FRED integration for a

future release.

• **Pattern-derived dates approximate the real release dates.**

BLS/BEA/ISM release dates vary +/- 1-2 days from the pattern; the tool flags these with `~`.

• **Regime-conditional reactions.** Historical stats are

unconditional; CPI moves the tape harder in inflation regimes than in disinflation. A conditioned version is a clean extension.

• **FOMC schedule is hardcoded for 2026.** Regenerate at year-end.