Macro Scenario Analysis API

Classify ISM Manufacturing PMI releases into actionable trading scenarios. GOLDILOCKS · MODERATE · SOFT_LANDING · CONTRACTION · AMBIGUOUS

Live Site

Landing page: https://473185670.github.io/macro-scenario-api/

Live API (Render, warm 24/7): https://macro-scenario-api.onrender.com

RapidAPI: https://rapidapi.com/category/Finance

Free Strategy Guides (6-page SEO cluster)

Guide	URL
Hub — All Guides	https://473185670.github.io/macro-scenario-api/macro-trading-guides.html
ISM PMI Trading Strategy	https://473185670.github.io/macro-scenario-api/ism-pmi-trading-strategy.html
Macro Trading Journal Template	https://473185670.github.io/macro-scenario-api/macro-trading-journal-template.html
Goldilocks Economy Trading	https://473185670.github.io/macro-scenario-api/goldilocks-economy-trading.html
Contraction Trading Strategy	https://473185670.github.io/macro-scenario-api/contraction-trading-strategy.html
Soft Landing Trade	https://473185670.github.io/macro-scenario-api/soft-landing-trade.html
Backtest Simulator	https://473185670.github.io/macro-scenario-api/macro-scenario-backtest.html

Products

• Notion Template ($12): https://4043969836017.gumroad.com/l/nztlu
• HTML Dashboard ($9.99): https://4043969836017.gumroad.com/l/pakci
• Complete Bundle ($29.99): https://4043969836017.gumroad.com/l/txmuvz
• Notion Preview: https://pale-earth-1ab.notion.site/Macro-Catalyst-Trading-Journal-3b2bf3457ff381ec85fac20dfb726a0c

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Why this API exists

Why this API exists

Every month, the ISM Manufacturing PMI release moves markets. Traders manually read the headline, new-orders, and prices-paid numbers, then mentally bucket them into "risk-on" vs "risk-off" and decide what to do. This API automates that:

• Input: 3 numbers (headline, new_orders, prices_paid — all 0-100)
• Output: scenario classification, confidence score, sector-by-sector guidance, and a machine-readable list of trading actions.

No market-data dependencies. Pure logic. ~5ms per call.

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Endpoints

POST /classify_scenario

Request body:

{
  "headline": 55.6,
  "new_orders": 54.2,
  "prices_paid": 71.1
}

Response:

{
  "scenario": "GOLDILOCKS — Strong Growth, No Overheat",
  "scenario_code": "GOLDILOCKS",
  "bias": "RISK-ON",
  "confidence": 85,
  "confidence_breakdown": {"headline_strength": 40, "new_orders_strength": 30, "alignment": 15},
  "equity": "BUY dip. Cyclical rotation into Industrials, Materials, Small Caps.",
  "rates": "US10Y likely tests 4.80%+. Duration short.",
  "crypto": "BTC benefits from risk-on. Target $66k+.",
  "crdo": "Structural bid reinforced. Target $210-230.",
  "actions": [
    {"asset": "SPY/Equities", "direction": "BUY", "note": "...", "priority": "HIGH"},
    {"asset": "US10Y", "direction": "SHORT_DURATION", "note": "...", "priority": "MEDIUM"},
    {"asset": "BTC", "direction": "BUY", "note": "...", "priority": "MEDIUM"},
    {"asset": "CRDO", "direction": "BUY", "note": "...", "priority": "HIGH"}
  ],
  "inputs": {"headline": 55.6, "new_orders": 54.2, "prices_paid": 71.1},
  "surprise": {"headline_surprise": 1.1, "new_orders_surprise": 1.2, "prices_paid_surprise": 15.1, "label": "BEAT"}
}

POST /ism_report

Same input, returns a full Markdown report:

{"report": "# ISM Manufacturing PMI Reaction Report\n..."}

GET /health

{"status": "ok", "version": "1.0.0"}

---

Scenario Logic

Condition	Scenario	Bias	Confidence
headline ≥ 55 AND new_orders ≥ 54	GOLDILOCKS	RISK-ON	85%
headline ≥ 52 AND new_orders ≥ 50	MODERATE	NEUTRAL-SLIGHT-RISK-ON	70%
headline ≥ 50 AND new_orders < 50	SOFT_LANDING	CAUTIOUS	65%
headline < 50	CONTRACTION	RISK-OFF	90%
otherwise	AMBIGUOUS	HOLD	40%

Consensus: headline 54.5, new_orders 53.0, prices_paid 56.0. Surprise label: BEAT if > +0.3, MISS if < −0.3, else IN-LINE.

---

Local Development

cd products/rapidapi_macro_scenario
pip install -r requirements.txt

# Run tests (no pytest needed)
python test_engine.py

# Start server
uvicorn main:app --reload --port 8000
# Open http://localhost:8000/docs  (Swagger UI)

---

Deploy to Render.com (free tier)

1. Push this directory to a GitHub repo (or the whole Arbitrage repo).
2. Go to https://render.com → New → Web Service → connect repo.
3. Render auto-detects render.yaml. Confirm and deploy.
4. Your API lives at https://macro-scenario-analysis-api.onrender.com.
5. Set RAPIDAPI_PROXY_SECRET env var (optional, for gateway auth).

Free tier: 750 hours/month, sleeps after 15min idle. Sufficient for API testing. For production, upgrade to Starter ($7/mo) — no sleep, always-on.

---

Register on RapidAPI

1. Go to https://rapidapi.com → Sign in → "Add API".
2. API Name: Macro Scenario Analysis
3. Base URL: your Render URL (e.g. https://macro-scenario-analysis-api.onrender.com)
4. Endpoints to expose:
   • POST /classify_scenario — "Classify ISM PMI into trading scenario"
   • POST /ism_report — "Full ISM reaction report (Markdown)"
   • GET /health — "Health check"
5. Pricing:
   • Free tier: 100 requests/month
   • Pro: $0.01 per request above free tier
   • Mega: $20/month for 5,000 requests
6. Categories: Finance, Data, Machine Learning
7. Publish. RapidAPI handles billing, rate-limiting, and key management.

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RapidAPI Listing Copy (paste into the listing form)

Short description (≤100 chars):

Classify ISM Manufacturing PMI releases into trading scenarios with confidence scores.

Long description:

Every month, the ISM Manufacturing PMI release moves global markets. This API
classifies the release into one of five trading scenarios — GOLDILOCKS, MODERATE
EXPANSION, SOFT LANDING RISK, CONTRACTION, or AMBIGUOUS — and returns:

- Scenario code + human-readable name
- Risk bias (RISK-ON / NEUTRAL / CAUTIOUS / RISK-OFF)
- Confidence score (0-100) with breakdown
- Sector-by-sector guidance (equities, rates, crypto, AI interconnect)
- Machine-readable trading actions list (asset, direction, priority, note)
- Consensus surprise computation (BEAT / MISS / IN-LINE)

Pure logic, no external data calls — sub-10ms response. Perfect for:
- Automated trading signal generation
- Macro research dashboards
- Backtesting ISM-reaction strategies
- Embedding in Discord/Slack/Telegram trading bots

Input: three ISM indices (headline, new_orders, prices_paid), each 0-100.
Output: full scenario analysis JSON or Markdown report.

Tags: ism, pmi, macro, trading, scenario, manufacturing, finance

---

Files

File	Purpose
scenario_engine.py	Core classification logic (no deps, reusable)
main.py	FastAPI app with 3 endpoints
test_engine.py	19 unit tests (run without pytest)
requirements.txt	Python deps
render.yaml	Render.com deploy config
README.md	This file

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Revenue Model

• Price: $0.01/call (free tier: 100 calls/mo)
• Marketplace: RapidAPI (3M+ developers)
• Maintenance: ~zero (pure logic, no data deps to break)
• Projected: 500 visitors/mo × 10% active × ~100 calls = ~$50/mo

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Built by Macro Edge Bot — Revenue Pipeline Node 💳 SOL: DiXt5GSxLW47szTATVGyF3vsj9g8YTGBQJj4BrQUST2y