Methodology

How M3I Research scores geopolitical risk and market stress

1. Overview

M3I Research is a hybrid geopolitical risk + market stress scoring platform. It combines curated qualitative intelligence (updated every 3 hours) with live market-derived signals to produce a composite Score of Scores (SOS) for investors tracking macro risk during active conflicts.

The system was built specifically for the 2026 US-Iran conflict but is designed to generalize to any resource-war scenario.

2. Score of Scores (SOS) — Composite Index

The SOS is a weighted average of 5 sub-inputs:

War Risk (25%) — Qualitative assessment of military escalation probability based on diplomatic signals, military posture, and historical conflict patterns
Market Turbulence (15%) — Composite of 11 independent market stress signals (see below)
Ceasefire Risk (20%) — Probability of ceasefire collapse, informed by diplomatic developments and market spread analysis
Hormuz Shipping (20%) — Strait of Hormuz disruption severity based on vessel traffic data, AIS monitoring, and news sentiment
7-Model Scanner Average (20%) — Average of all 7 analytical models in the system

Regime thresholds:

0–29 LOW 30–49 MODERATE 50–69 ELEVATED 70–100 HIGH

When curated data is fresh (updated within 12 hours), qualitative scores take priority. When stale, the live market engine computes proxy scores from real-time data.

3. The 7 Models

MODEL 01

War Resolution

Probability of diplomatic resolution within defined timeframes. Incorporates historical war pattern analysis, diplomatic engagement level, and resource-war duration benchmarks.

MODEL 02

Market Turbulence

11-signal composite measuring real-time market stress. Signals include VIX, credit spreads, oil volatility, equity drawdowns, safe-haven flows, and sector rotation patterns.

MODEL 03

Recession Risk

Probability of US recession driven by energy price shocks, consumer spending compression, and monetary policy constraints.

MODEL 04

Escalation Risk

Probability of conflict intensification beyond current parameters. Tracks military posture changes, proxy activations, and nuclear-threshold indicators.

MODEL 05

V-Shape Recovery

Probability of rapid market recovery upon conflict resolution. Based on historical post-war recovery patterns and current structural damage assessment.

MODEL 06

Historic Dip Zone

Whether current market levels represent a historically significant buying opportunity relative to geopolitical risk.

MODEL 07

Hormuz Shipping

Strait of Hormuz disruption severity. Combines AIS vessel tracking data, news-derived headline sentiment, and structural closure indicators.

4. Historical War Pattern Engine

The Pattern Engine analyzes 13 US conflicts since 1861 to identify resolution patterns. Key insight: resource wars (oil, shipping lanes) resolve approximately 21x faster than ideological wars (avg 103 days vs 2,340 days). The engine classifies the current conflict as a resource war and applies compressed timeline probabilities.

Dataset: 4 resource wars, 7 ideological, 2 occupation. 6 of 12 completed wars had failed ceasefires before resolution.

Known limitations: Small historical dataset (13 conflicts). The current conflict involves a nuclear-threshold state — no previous US resource war had this dimension. The Pattern Engine explicitly flags this as uncharted territory in its bear case.

5. Live Engine vs Curated Scores

The site operates in hybrid mode:

Curated scores are updated every 3 hours by the M3I analytical engine, incorporating qualitative intelligence that pure market signals cannot capture (e.g., diplomatic developments, military posture changes)
Live market engine runs every 5 minutes, computing proxy scores from real-time market data (VIX, Brent-WTI spread, gold, BTC, etc.)
When curated data is fresh, curated scores control the SOS display. When stale, the live engine takes over.

6. Data Sources

Market data: Yahoo Finance (real-time)
Hormuz vessel tracking: AIS data, news-derived estimates
Geopolitical intelligence: Multi-source news aggregation (Reuters, CNBC, Al Jazeera, CNN, Bloomberg, etc.)
Historical conflict data: Congressional Research Service, academic databases

7. Limitations

Small dataset: 13 US conflicts. Non-US and proxy conflicts not yet incorporated.
Nuclear-threshold gap: No historical analog for a US resource war against a nuclear-threshold state.
Proprietary calibration: Individual signal weights and calibration constants are not published.
Single-conflict optimization: Built for the 2026 US-Iran conflict. Generalization to other conflict types is untested.
Not financial advice: M3I scores are analytical outputs, not investment recommendations.

8. API Access

Open-source API available on GitHub. MIT licensed. No authentication required.

Repository: github.com/m3iresearch8/m3i-api

Endpoint: m3iresearch.com/api/scores.json